Risk Assessment Approach Research Articles

Localised multi-hazard risk assessment in Kyrgyz Republic

One of the key tasks in ensuring national security is the ability of the state and society to recognise and effectively assess the conditions for disasters, and to prevent them from threatening the sustainable development of the country. The Kyrgyz Republic is highly vulnerable to the influence of climate change, which in turn affects the frequency and intensity of disasters. The Kyrgyz Republic is exposed to almost all types of geological and man-made hazards, including earthquakes, landslides, debris flows, flash floods, outbursts of mountain lakes, dam failures, avalanches, droughts, extreme temperature, epidemics and releases of hazardous substances. Analysis of information on existing risks and their control systems used to reduce their negative impact makes it possible to assess the degree of probability, the expected consequences of threats, determine the degree of risk, the adaptive potential of communities and select appropriate protective measures. Therefore, this study is conducted to assess the hazard, vulnerability and exposure of Suzak district (Jalal-Abad oblast) in order to quantify the risk of the study area using multi-parameter holistic assessment with field collecting of primary data and utilizing Index-based Risk Assessment approach based on applying INFORM Risk model. Collected data was used to downscale subnational INFORM Risk model for municipal and district level using a multi-layered structure. A risk score is calculated by combining 72 indicators that measure three main dimensions: hazard & exposure, vulnerability, and lack of coping capacity. These findings provide an opportunity to develop a more effective disaster risk management at the local and national levels, by prioritizing relevant actions and investments for municipalities – districts which are demonstrated relatively highest risk scores. Also, the possibility of applying localized risk assessment procedures provides an opportunity to obtain more accurate sub-national (district/oblast based) and national levels with effective assessing dynamics of risk.

Evaluating the Prognostic and Clinical Validity of the Fall Risk Score Derived From an AI-Based mHealth App for Fall Prevention: Retrospective Real-World Data Analysis.

Falls pose a significant public health concern, with increasing occurrence due to the aging population, and they are associated with high mortality rates and risks such as multimorbidity and frailty. Falls not only lead to physical injuries but also have detrimental psychological and social consequences, negatively impacting quality of life. Identifying individuals at high risk for falls is crucial, particularly for those aged ≥60 years and living in residential care settings; current professional guidelines favor personalized, multifactorial fall risk assessment approaches for effective fall prevention. This study aimed to explore the prognostic validity of the Fall Risk Score (FRS), a multifactorial-based metric to assess fall risk (using longitudinal real-world data), and establish the clinical relevance of the FRS by identifying threshold values and the minimum clinically important differences. This retrospective cohort study involved 617 older adults (857 observations: 615 of women, 242 of men; mean age 83.3, SD 8.7 years; mean gait speed 0.49, SD 0.19 m/s; 622 using walking aids) residing in German residential care facilities and used the LINDERA mobile health app for fall risk assessment. The study focused on the association between FRS at the initial assessment (T1) and the normalized number of falls at follow-up (T2). A quadratic regression model and Spearman correlation analysis were utilized to analyze the data, supported by descriptive statistics and subgroup analyses. The quadratic model exhibited the lowest root mean square error (0.015), and Spearman correlation analysis revealed that a higher FRS at T1 was linked to an increased number of falls at T2 (ρ=0.960, P<.001). Subgroups revealed significant strong correlations between FRS at T1 and falls at T2, particularly for older adults with slower gait speeds (ρ=0.954, P<.001) and those using walking aids (ρ=0.955, P<.001). Threshold values revealed that an FRS of 45%, 32%, and 24% corresponded to the expectation of a fall within 6, 12, and 24 months, respectively. Distribution-based minimum clinically important difference values were established, providing ranges for small, medium, and large effect sizes for FRS changes. The FRS exhibits good prognostic validity for predicting future falls, particularly in specific subgroups. The findings support a stratified fall risk assessment approach and emphasize the significance of early and personalized intervention. This study contributes to the knowledge base on fall risk, despite limitations such as demographic focus and potential assessment interval variability.

Application of Three-Dimensional Risk Matrix Approach for Occupational Injury Risk assessment in an Automotive Factory

Introduction: Risk assessment matrix is a tool used in a project’s risk assessment process to identify the probability of risks and evaluate the potential damages caused by those risks. Generally, a risk assessment matrix is drawn in a two-dimensional form, with two factors: the severity of the accident and the probability of its occurrence. So, the purpose of this study is to develop a specific risk assessment matrix in a three- dimensional form by using the accident severity grade (ASG) rating system, the accident probability, and taking into account the preventive approach that helps occupational injury risk assessment in the automobile industry. Material and Methods: This cross-sectional study was conducted in 1402 (2023) in one of the automobile assembly industries. One hundred cases were randomly selected by examining the reports of this industry’s past accidents. The ASG scoring checklist was designed and completed by the experts to assess the severity of accidents. Then, considering the ASG score, the frequency of the accident, and its preventability, a three-dimensional risk assessment matrix specific to this industry was presented. Results: According to the findings of the accident analysis, a total of 658 accidents and 15,019 lost working days were recorded in this period. The most influential factor in the occurrence of accidents is related to “surface condition” (influence factor = 0.6), and the least of them belongs to the “weather conditions” (influence factor = 0.028). The results of the three-dimensional matrix show that when the ability to prevent accidents increases, the risk of accidents decreases. Conclusion: Using the accident severity grade (ASG) and preventability in the proposed three-dimensional risk assessment matrix, the accident severity can be quantified immediately after the accident. This approach allows monitoring workplaces during the accident, leading to timely control and risk management implementation.

Assessing the Causal Role of Walking Pace and Hand Grip Strength with Chronic Obstructive Pulmonary Disease Hospital: A Mendelian Randomization Study

Background Chronic obstructive pulmonary disease(COPD) hospitalization heightens risks for patients, including mortality, reduced quality of life, and financial strain. Walking pace (WP) and hand grip strength (HGS) are key indicators, their direct connection to COPD hospitalization is uncertain. Objective To investigate the relationship between genetic determinants of walking pace, hand grip strength, and the risk of COPD hospitalization as well as lung function. Methods The data pertaining to WP (n = 459,915), HGS (n = 922,115), COPD hospitalizations (n = 309,154), and lung function (n = 79,055) were procured from comprehensive large-scale genome-wide association studies. In carrying out the causal inference analysis, robust statistical methods were utilized, encompassing inverse variance weighted (IVW), MR-Egger, weighted median, simple median and Weighted mode. To address issues of heterogeneity, pleiotropy, and outliers, we incorporated sensitivity analyses and Mendelian randomization (MR) techniques. Results The IVW analysis suggests that a faster WP reduces the risk of COPD hospitalization (OR = 0.3559, 95% CI: 0.22-0.52; p = 5.197 × 10−5). It also reveals a potential association between gait speed and the likelihood of developing early-onset COPD (OR = 0.189, 95% CI 0.09 to 0.39; p = 8.89 × 10-6) as well as late-onset COPD (OR = 0.44, 95% CI 0.25 to 0.76; p = 0.0036). The IVW analysis further indicates a potential correlation between an increased WP and enhanced peak expiratory flow (PEF) (OR = 1.699, 95% CI: 1.23 to 2.35; p = 0.0014), forced expiratory volume in 1 s(FEV1, OR = 1.557, 95% CI 1.24 to 1.95; p = 0.0001), and forced vital capacity(FVC, OR = 1.584, 95% CI 1.26 to 1.99; p = 8.89 × 10-5). The IVW analysis suggests a possible causal link between stronger left-hand grip strength and elevated levels of FVC (OR = 1.29, 95% CI: 1.15 to 1.46; p = 1.68 × 10-5), FEV1 (OR = 1.24, 95% CI: 1.11 to 1.39; p = 1.63 × 10-4), and PEF (OR = 1.2, 95% CI: 1.07 to 1.36; p = 2.67 × 10-3). Similarly, right-hand grip strength exhibits a comparable causal relationship with FVC and PEF as left-hand grip strength. Conclusions Our research shows a link between slower walking pace and higher COPD hospitalization risk, as well as decreased lung function (PEF, FEV1, FVC). We also found a significant correlation between weaker hand grip and reduced lung function, especially FVC. These findings have the potential to improve risk assessment approaches, intervention strategies, and management methods for COPD patients, while simultaneously enhancing their overall quality of life and health status.

Safety evaluation of the food enzyme β-fructofuranosidase from the non-genetically modified Saccharomyces cerevisiae strain CNCM I-3399.

The food enzyme β-fructofuranosidase (β-d-fructofuranoside fructohydrolase; EC 3.2.1.26) is produced with the non-genetically modified Saccharomyces cerevisiae strain CNCM I-3399 by Kerry Ingredients & Flavours Ltd. The production strain qualifies for the qualified presumption of safety (QPS) approach for risk assessment. The food enzyme is intended to be used in four food manufacturing processes. Exposure was estimated to be up to 2.485 mg total organic solids/kg body weight (bw) per day in European populations. As the production strain qualifies for QPS, and in the absence of other concerns, the Panel considered that toxicological studies were not needed for the safety assessment of this food enzyme. A search for homology of the amino acid sequence of the food enzyme to known allergens was made and one match with a tomato allergen was found. The Panel considered that the risk of allergic reactions upon dietary exposure to this food enzyme, particularly in tomato allergic individuals, cannot be excluded, but the likelihood is low. Based on the data provided, the Panel concluded that this food enzyme does not give rise to safety concerns, under the intended conditions of use.

Risk Management of Engineered Nanomaterials at Workplaces: A Narrative Review on Available Frameworks and Tools

Introduction: Due to uncertainties regarding the risks of engineered nanomaterials for human health and the environment, different organizations and researchers have developed various management frameworks and assessment tools to mitigate hazards during the procedures and applications of engineered nanomaterials. However, most of these techniques do not meet all the individual requirements. This study provides a review and introduction to the techniques developed for the management of safety, health, and environmental risks associated with engineered nanomaterials. Material and Methods: In order to find pertinent documents on the safe handling of engineered nanomaterials, a search was conducted using the following keywords: “Engineered nanomaterials”, “Framework”, “Tool”, “Risk management”, “Occupational exposure”, “Environment”, “Risk assessment”, and “Nanotechnology”. The search was conducted on various databases, including Scopus, Web of Science, NIOSH, ECHA, and ISO. Among the search results, tools and frameworks that specifically focus on the safety, health, and environmental risk management or assessment of engineered nanomaterials were selected. Results: Among the search results, 17 frameworks and 11 developments in the field of managing occupational, environmental, and toxicological risks associated with engineered nanomaterials were discussed. Various frameworks and tools for identifying, evaluating, and managing the potential risks of engineered nanomaterials vary in terms of their scope, goals, risk assessment approaches, and output, offering diverse applications. Conclusion: Various tools and frameworks, each with unique properties, applications, and limitations, can assist organizations in achieving their goals related to safety, health, and environmental issues in the field of nanotechnology. Currently, there is no consensus on the optimal approach for assessing the risks of nanomaterials, underscoring the necessity for additional research, development, and collaboration in this field.

A novel data-driven approach for proactive risk assessment in shield tunnel construction

A novel data-driven approach for proactive risk assessment in shield tunnel construction

A framework for large-scale risk assessment of road-related impacts, with application to mustelids

Roads, while crucial for human development and economic growth, pose significant threats to biodiversity. Large-scale road risk assessments are essential for guiding infrastructure planning, particularly in identifying areas to avoid new construction or prioritizing regions for mitigation where road networks are already established. However, conducting comprehensive assessments is challenging in regions with limited data on species’ responses to roads. In this study, we propose a methodological approach for global and regional risk assessments of road-related impacts, utilizing data on road exposure and species-level susceptibility to road effects. We first derive species-specific susceptibility to road impacts using available trait data and expert knowledge. This information is spatialized through species range maps, creating a cross-taxa susceptibility layer. We then combine this layer with infrastructure density data to produce a bivariate map that highlights the co-occurrence of susceptibility and exposure. Through this approach, we identify priority mitigation areas—regions with high susceptibility and high exposure where mitigation efforts should be concentrated—and priority preservation areas—regions with high susceptibility but low exposure that should be protected from further road development. Our case-study focuses on mustelids, a globally distributed group with significant vulnerability to road impacts yet underrepresented in road ecology studies. The results reveal that the highest-risk areas are concentrated in Eastern Europe, Southeast Asia, and scattered across sub-Saharan Africa, where high conservation value intersects with extensive road networks, marking these as priority mitigation areas. Priority preservation areas span mainly across South America, North America, and Siberia, with some areas across Africa and Borneo. This framework offers a foundation for preliminary assessments and proactive zoning, aiding in the identification of conservation management areas across different infrastructure types and taxa. Its adaptability makes it a valuable tool for researchers, wildlife managers, and transportation planners conducting large-scale assessments of infrastructure impacts on biodiversity.

Gender disparity in health-related quality of life among people living with HIV/AIDS in Ethiopia: a systematic review and meta-analysis.

Health-related quality of life (HRQoL) is a key outcome indicator in antiretroviral therapy program. In Ethiopia, primary studies on gender disparity in HRQoL among people living with HIV/AIDS (PLHA) are conflicting, with no pooled estimation. Therefore, this study aimed to investigate gender disparity in HRQoL among PLHA in Ethiopia. Studies were retrieved from PubMed, Web of Science, SCOPUS, Embase, MEDLINE, Science Direct, HINARI, and PsycINFO were systematically searched. In addition, Google Scholar, Google, journal homepages, bibliographies, and universities' research repositories in the country were searched by combining keywords and Medical Subject Headings (MeSH) terms with Boolean operators. Based on the primary study results, the average score of each domain was utilized as a cut-off point to classify HRQoL as poor or good. The Joanna Briggs Institute (JBI) checklist was used to assess study quality. A random-effects model was used to report the pooled estimates. Summary estimates are presented in forest plots and tables. The variation between studies was assessed using the Higgins heterogeneity test (I2). Funnel plot, Begg's test, and Egger's test were used to assess publication bias. Data were extracted using Microsoft Excel and exported to STATA 17 (Corporation, College Station, TX, USA) for analysis. The search results were managed using the EndNote X7 software. Fifteen studies with 4,867 PLHA were included. The pooled prevalence of poor HRQoL was 46.53% (95% CI: 41.96-51.10), 46.15% (95% CI: 37.05-55.24), and 36.21% (95% CI: 30.19-42.23) among PLHA, women, and men living with HIV, respectively. Moreover, a significant gender disparity in HRQoL was observed among Ethiopian women and men living with HIV. Women living with HIV were found to have 61% increased odds of poor HRQoL than men living with HIV in the country (OR = 1.61, 95% CI: 1.07, 2.15). No statistical evidence of a publication bias was observed. Almost half of PLHA patients in Ethiopia had a poor HRQoL. Women living with HIV have higher odds of poor HRQoL than men living with HIV. This highlights the pressing need for gender-specific risk assessment approaches and treatment interventions aimed at optimizing HRQoL in HIV/AIDS settings. https://www.crd.york.ac.uk/prospero/, identifier CRD42023454810.

Evaluation of Road Safety Hazard Factors in Egypt Using Fuzzy Analytical Hierarchy Order of Preference by Similarity to Ideal Solution Process

To address road accident losses, there is a need to prioritize safety factors, especially in high-risk locations on the road network, toward assuring a sustainable transport system. This paper proposes an approach for quantitative risk assessments of safety factors in hazardous road locations and involves the integration of the Fuzzy logic model, the Analytic Hierarchy Process (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This new innovative method offers a way to prioritize and select safety factors associated with hazardous locations using a hierarchical structure. To demonstrate the applicability of this method, a case study was conducted in Egypt. The assessment process involved active participation by professionals through multiple expert meetings. This collaborative approach ensures that the assessment incorporates valuable real-world knowledge and experiences. It analyzed road safety hazardous conditions across various sections, including intersections, non-intersection sections, narrow bridge sections, and curve sections. The application of FAHP-TOPSIS enables the determination of weights for safety factors within each section, facilitating the evaluation of safety indices between them and ranking the safety hazard sections. The achieved analysis revealed that the hazard safety factor index is comparatively higher in curved sections compared to other types of sections. Light utility poles and road barriers significantly affected the hazard index. By utilizing this approach, governments may make informed decisions regarding the allocation of resources and the implementation of safety measures at hazardous road locations.

Rapid warning system to predict chemical hazards in wild European eel (Anguilla anguilla): Transcriptomic approach in food risk assessment

Heavy metals present in fish muscle pose a risk to consumers. Biomarkers could reveal the accumulation of these toxic contaminants early without having to resort to muscle analysis. In this study, a specific objective was pursued: to identify biomarkers to be proposed as sensitive tools in risk assessment analyzes using European eels as sentinel animals, captured from four rivers in Salerno province (southern Italy). Among the four genes chosen for this analysis, that of Acyl-Peptide Hydrolase 2 (APEH2) seems to qualify as an excellent biomarker, whose transcriptional profile responds well even to small levels of toxic metals. Statistical analyses (ANOVA, PCA) have shown that variations in the expression of the APEH2 gene, both in the liver and in the gills of eels, could provide important information on the health status of the aquatic animal, on possible exposure to toxic heavy metals and on the quality and safety of the meat.

Alcohol-attributable deaths in Thai people from 2015 to 2021 using the comparative risk assessment approach.

The alcohol-attributable mortality rate is an important health indicator for surveillance of health-related impacts of alcohol consumption. This study aimed to estimate the annual number and rate of alcohol-attributable deaths among the Thai population aged 15 years and over during 2015-2021. Mortality data were drawn from the National Death Registry based on ICD-10. We used the standard methodology of comparative risk assessments for alcohol within the general framework of the Global Burden of Disease Studies and used alcohol-attributable fractions, derived from exposure, and relative risk compared to lifetime abstainers as the counterfactual. Age-standardization was used to adjust mortality rates which were calculated by cause, age group, and sex. The estimated annual number of alcohol-attributable deaths was 20,039 (men: 17,726 [6.50% of total annual deaths of the Thai population] and women: 2312 [1.11%]). The age-standardized alcohol-attributable mortality rates continuously increased from 33.8 to 37.5 deaths per 100,000 population from 2015 to 2019 and slightly decreased to 34.5 and 35.3 in 2020 and 2021, respectively. The three leading causes of death attributed to alcohol consumption were road injuries, cirrhosis and other liver diseases, and other unintentional injuries. Alcohol remains an important preventable cause of death among Thais. The alcohol-attributable mortality rate increased from 2015 to 2019 but declined in 2020 and 2021, possibly due to the coronavirus pandemic and lockdown measures. Culturally appropriate, cost-effective interventions should be used to control alcohol accessibility, particularly among young people who frequently sustain injuries from external causes and have high mortality rates.

Greenland Wind-Wave Bivariate Dynamics by Gaidai Natural Hazard Spatiotemporal Evaluation Approach

The current work presents a case study for the state-of-the-art multimodal risk assessment approach, which is especially appropriate for environmental wind-wave dynamic systems that are either directly physically observed or numerically modeled. High dimensionality of the wind-wave environmental system and cross-correlations between its primary dimensions or components make it quite challenging for existing reliability methods. The primary goal of this investigation has been the application of a novel multivariate hazard assessment methodology to a combined windspeed and correlated wave-height unfiltered/raw dataset, which was recorded in 2024 by in situ NOAA buoy located southeast offshore of Greenland. Existing hazard/risk assessment methods are mostly limited to univariate or at most bivariate dynamic systems. It is well known that the interaction of windspeeds and corresponding wave heights results in a multimodal, nonstationary, and nonlinear dynamic environmental system with cross-correlated components. Alleged global warming may represent additional factor/covariate, affecting ocean windspeeds and related wave heights dynamics. Accurate hazard/risk assessment of in situ environmental systems is necessary for naval, marine, and offshore structures that operate within particular offshore/ocean zones of interest, susceptible to nonstationary ocean weather conditions. Benchmarking of the novel spatiotemporal multivariate reliability approach, which may efficiently extract relevant information from the underlying in situ field dataset, has been the primary objective of the current work. The proposed multimodal hazard/risk evaluation methodology presented in this study may assist designers and engineers to effectively assess in situ environmental and structural risks for multimodal, nonstationary, nonlinear ocean-driven wind-wave-related environmental/structural systems. The key result of the presented case study lies within the demonstration of the methodological superiority, compared to a popular bivariate copula reliability approach.

Risk assessment of homologous variants of biotech trait proteins using a bridging approach

ABSTRACT A transgenic protein is frequently expressed as different homologous variants in genetically modified crops due to differential processing of targeting peptides or optimization of activity and specificity. The aim of this study was to develop a science-based approach for risk assessment of homologous protein variants using dicamba mono-oxygenase (DMO) as a case study. In this study, DMO expressed in the next-generation dicamba-tolerant maize, sugar beet and soybean crops exhibited up to 27 amino acid sequence differences in the N-terminus. Structure modeling using AlphaFold, ESMFold and OpenFold demonstrates that these small N-terminal extensions lack an ordered secondary structure and do not disrupt the DMO functional structure. Three DMO variants were demonstrated to have equivalent immunoreactivity and functional activity ranging from 214 to 331 nmol/min/mg. Repeated toxicity studies using each DMO variant found no test substance-related adverse effects. These results support that homologous protein variants, which have demonstrated physicochemical and functional equivalence, can leverage existing safety data from one variant without requiring additional de novo safety assessments.

FMI-CAECD: Fusing Multi-Input Convolutional Features with Enhanced Channel Attention for Cardiovascular Diseases Prediction.

Cardiovascular diseases (CVD) have become a major public health problem affecting the national economy and social development, and have become one of the major causes of death. Therefore, the prevention, control and risk assessment of CVD have been increasingly emphasized. However, current CVD prediction models face limitations in capturing complex relationships within physiological data, potentially hindering accurate risk assessment. This study addresses this gap by proposing a novel Framework for Multi-Input, One-dimensional Convolutional Neural Network (1D-CNN) with Attention Mechanism for CVD (FMI-CAECD). This framework leverages the feature extraction capabilities of Convolutional Neural Network (CNN) alongside an Attention Mechanism to adaptively identify critical features and non-linear relationships within the data. Additionally, Shapley Additive Explanations (SHAP) analysis is incorporated to provide deeper insights into individual feature importance for disease prediction. Performance evaluation on the BRFSS 2022 dataset demonstrates that FMI-CAECD achieves superior accuracy (97.45%), sensitivity (96.84%), specificity (95.07%), and F1-score (92.44%) compared to traditional machine learning baselines and other deep learning models. These findings suggest that FMI-CAECD offers a promising approach for CVD risk assessment.

Burden of major cancers in China attributable to modifiable risk factors: Predictions from 2012 to 2035.

The cancer burden continues to escalate in China. This study was designed to quantify the burden of deaths attributable to modifiable risk factors for major cancers in China from 2012 to 2035, and to provide evidence-based recommendations for cancer management. Using nationally representative data on risk factors and cancer mortality, a comparative risk assessment approach was employed to calculate the temporal trend of population-attributable fractions (PAFs) for 15 modifiable risk factors associated with major cancers in China. The PAF for modifiable risk factors decreased from 64.5% (95% uncertainty interval [UI]: 46.2%-75.3%) in 2012 to 59.3% (95% UI: 40.6%-71.2%) in 2035. Attributable deaths increased from 1,309,990 (95% UI: 938,217-1,529,170) in 2012 to 1,313,418 (95% UI: 898,411-1,577,189) in 2035, while attributable disability-adjusted life years (DALYs) rose from 28,488,120 (95% UI: 20,471,859-33,308,237) to 33,017,705 (95% UI: 22,730,814-39,564,735). Between 2012 and 2035, the top three risk factors contributing to cancer burden shifted from smoking, insufficient fruit intake and particulate matter <2.5 μm in diameter (PM2.5) exposure to smoking, physical inactivity, and inadequate fruit intake. Controlling modifiable risk factors at recommended levels by 2020 could have prevented around 890,000 deaths and 2.2 million DALYs by 2035. The proportion of cancer burden due to modifiable risk factors is projected to decrease, but the absolute number continues to rise. Adhering to an optimal lifestyle could prevent ~40% of cancer deaths by 2035. Key modifiable risk factors including smoking, physical inactivity, and insufficient intake of fruits require high attention.

Towards a comprehensive methodology for ecotoxicological assessment: Prioritizing plant protection products for mixture testing in edge-of-field surface waterbodies

Pesticide applications in agriculture result in complex mixtures of Plant Protection Products (PPPs) in the environment. The ecotoxicological effects of these mixtures can occur at concentrations considered safe for individual chemicals, indicating potential risks underestimated by current regulatory assessments focused on individual active ingredients. To address this challenge, our study introduces a methodology for identifying priority PPPs for formulating mixtures, enabling further ecotoxicological testing in water and sediment compartments of edge-of-field surface water bodies, targeting pelagic and benthic organisms. This methodology was primarily based on the actual quantification of PPPs present in these compartments from selected case study sites (CSSs) in Europe and Argentina (11 and 4 for water and sediments, respectively). A conceptual framework was developed that discriminates and selects concerning PPPs based on their individual risk quotient and frequency of occurrence in each CSS, drawing upon two EU regulatory risk assessment approaches, i.e., the general approach under REACH for any environmental contaminant of concern – the European Chemicals Agency (ECHA) approach; and that specifically focusing on PPPs – the European Food Safety Authority (EFSA) approach. Irrespective of whether the focus is on water or sediments, the study revealed disparities in PPP rankings depending on the approach used to identify PPPs of concern, with the ECHA approach being more conservative than the EFSA approach. Despite this, the EFSA approach follows a more standardized assessment factor definition strategy, potentially allowing avoidance of risk overestimation, as well as resulting in a more balanced representation of different PPP classes for subsequent mixtures testing. Overall, the methodological development reported herein, along with the inconsistencies found when comparing different regulatory approaches to assess the risk of environmental contaminants, highlight the need for further discussion on the most appropriate directions towards the standardization of the regulatory risk assessment of PPP mixtures.

Assessing the contributions of gender, clinical symptoms, and psychometric traits to non-suicidal self-injury behaviors in Chinese adolescents: a nomogram approach.

Non-suicidal self-injury (NSSI) behaviors among adolescents with mood disorders represent a significant global public health concern. This study aimed to assess the prevalence and identify key predictors of NSSI behaviors in Chinese adolescents diagnosed with depressive or bipolar disorders, addressing a critical gap in the literature. Data from 2343 participants in the Chinese Adolescent Depression Cohort (CADC) were analyzed. The study employed a comprehensive approach, utilizing medical records, clinical assessments, and validated psychometric instruments. Statistical analyses included chi-square tests, logistic regression, and ROC curve analyses, culminating in the development of a predictive nomogram. The prevalence of NSSI behaviors was strikingly high at 73.32%. Significant predictors included female gender (AOR = 2.14, 95% CI [1.70, 2.68]), presence of hallucinations (AOR = 1.52, 95% CI [1.18, 1.97]), borderline personality features (AOR = 1.03, 95% CI [1.01, 1.08]), and childhood trauma (AOR = 1.02, 95% CI [1.01, 1.03]). The study's key contribution is a predictive nomogram with an AUC of 0.74, demonstrating good efficacy in predicting NSSI behaviors. This research reveals an alarmingly high prevalence of NSSI behaviors in Chinese adolescents with mood disorders and identifies critical predictors spanning demographic, clinical, and psychometric domains. The developed nomogram offers a novel approach for risk assessment, highlighting the importance of comprehensive evaluations in adolescent mental healthcare. These findings have significant implications for developing targeted interventions and improving risk assessment strategies in clinical practice.

Use of serum-free media for peripheral blood mononuclear cell culture and the impact on T and B cell readouts.

As part of a wider programme of work developing next-generation risk assessment approaches (NGRA) using non-animal methods (NAMs) for safety assessment of materials, Unilever SEAC is exploring the use of a peripheral blood mononuclear cell (PBMC) system to investigate how cells from different arms of the human immune system are impacted by different treatments. To maximise human relevance, the cell cultures are supported by human serum, but this came with some challenges, including an inability to measure induced levels of immunoglobulins due to high background levels. Therefore, a study comparing use of human sera containing media with three different chemically defined serum-free media was undertaken. PBMC were isolated from healthy donors and cultured in the absence (media alone) or presence of stimulation reagents (CpG-ODN plus IL-15, Pokeweed Mitogen (PWM) or Cytostim (CS)), in RPMI plus human serum, AIM-V, CTS OpTmizer T cell expansion SFM or X-VIVO 15 media. T cell (CD4+ and CD8+) and B cell proliferation and viability were measured after 6days, along with levels of total IgG in the cell culture supernatants. Each of the serum-free media tested supported good levels of viable and proliferating T cells and B cells over the 6 days of culture, with only a few, small differences across the media, when there was no stimulation. They also enabled detection of a stimulation-evoked increase in IgG levels. There were however some differences in the viability and proliferation responses of T and B cells, to different stimuli, across the different media. The serum-free media formulations tested in this study offer defined systems for. measuring B cell IgG responses, in vitro, in either a 'T cell-independent' (CpG + IL-15) or "T cell-dependent" (PWM or CS) manner and for assessing B cell proliferation, particularly in response to a "T cell-independent" stimulus. However, there are some characteristics and features endowed by human serum that appear to be missing. Therefore, further work is required to optimise animal-free, chemically defined culture conditions for PBMC based assays for inclusion in tiered safety assessments.

Dynamic energy management and control of networked microgrids based on load to grid services and incentive-based demand response programs: A multi-agent deep reinforcement learning approach

This study has presented the energy management paradigm in a networked microgrid structure based on L2G services and considering incentive-based load response (IBDR) programs and energy market requirements to reduce operating costs, control and restore voltage and frequency index, providing the benefits of subscribers and distribution system operators. In this study, multi-objective functions such as optimal operation based on IBDR structure and energy market requirements, risk assessment, and L2G service approach are configured in the framework of central and local controllers. Optimal operation and risk assessment are analyzed by a multi-task learning algorithm based on multi-objective function and L2G service policies are evaluated based on multi-agent deep reinforcement learning. Control policies are sent by the communication system to the components affecting the optimal power distribution as well as the voltage and frequency controllers. L2G services have been evaluated in different scenarios such as plug-and-play operating conditions, load fluctuations, and operating in island mode. The results of optimal operation based on L2G services show that the IBDR program implementation reduces the total operation cost by 21%. Also, the total operating cost of the proposed framework is 13.97% less than the RL method and 27.8% less than the ANN method.