Safety Assessment Tool Research Articles

Use of Fruit Waste as Natural Dyes in pH-Sensitive Colorimetric Sensors for Tilapia Fillets Quality Decline

Graphical Abstract Highlight Research 1. The use of dragon fruit peel, mangosteen peel and onion peel waste as natural dyes in colorimetric sensors was analyzed in this study. 2. Natural dyes are added to bioplastics with kappa carrageenan polymer, a mixture of corn starch and kappa carrageenan, and corn starch to determine the characteristics of the best bioplastic to be used as a colorimetry sensor. 3. The quality of the fish fillet compared to the color changes in colorimetry sensor was analysed in this study. 4. Mixture of kappa carrageenan and corn starch as bioplastic with casting method was analyzed in this study. Abstract Tilapia fillet aimed to prolonging shelf life, may still experience quality deterioration posing food safety risks. Colorimetric pH indicators offer a simple and affordable solution to the food industry to evaluating fish spoilage. Natural dyes reduce potential health risks associated with synthetic dyes. Anthocyanin sources haven’t been explored like dragon fruit rind, mangosteen rind, and red onion skin serve as real time quality and safety assessment tools for consumers. This study explores the potential of anthocyanin extracted from dragon fruit rind, mangosteen rind, and red onion skin as colorimetric sensors for evaluating the quality and safety of tilapia fillets. The anthocyanin-based sensors developed using kappa carrageenan and corn starch polymers to achieve sustainability fisheries program and were characterized according to the Japanese Industrial Standard for bioplastics. The results show that anthocyanin from dragon fruit skin exhibited the best color change in response to pH changes in the tilapia fillet, indicating its potential as a reliable indicator of spoilage. This research highlights the feasibility of using natural dyes as colorimetric sensors, reducing the risk of health hazards associated with synthetic dyes. This study also shows that different polymers give different characteristic of bioplastic. Carrageenan bioplastic shows best thickness values of 0,118 mm; Carrageenan and corn starch bioplastics shows best tensile strength values of 20,62 MPa; Carrageenan bioplastic shows best elongation values of 254%; and All polymers shows the same biodegradation rate values of 14,29%. Further studies are needed to explore other natural dyes and optimize the polymers for optimal bioplastic characteristics.

212P BRGSF-HIS mice as a predictive tool for safety assessment of biologics

212P BRGSF-HIS mice as a predictive tool for safety assessment of biologics

Health, safety and environmental risk assessment tool applied to site selection for geological hydrogen storage in saline aquifers

Hydrogen (H2) emerges as a pivotal player in the transition to renewable energy sources. To address the seasonal fluctuations in energy dynamics, underground storage emerges as the most efficient approach, and saline aquifers within sedimentary basins as promising repositories for substantial H2 volumes. However, this potential storage solution remains relatively unexplored. Conducting a comprehensive health, safety, and environment (HSE) risk assessment is vital for the technological advancement and public acceptance of geological H2 storage sites. This study introduces a methodology designed to select and classify potential formations based on their HSE risks, offering a safety-oriented approach to identifying suitable storage sites. The proposed methodology underwent testing in two deep saline aquifers located in distinct geological contexts within the Iberian Peninsula. The aim of this study is to establish a foundation for further investigations and implementation of geological H2 storage sites while ensuring safety and adhering to environmental and health standards.

Development and psychometric validation of a patient safety assessment tool in German Radiation Oncology: the PaSaGeRO Study protocol

IntroductionEnsuring patient safety in radiation oncology is crucial for delivering high-quality healthcare. Patient safety indicators (PSIs) provide a mechanism for identifying, quantifying and evaluating risks and the effectiveness of safety...

Critical Review of Hydrogen Safety Assessment Tools: Indian Perspective

Critical Review of Hydrogen Safety Assessment Tools: Indian Perspective

Development of a Nuclear Safety and Security Integration Assessment Tool for Research Reactors and Associated Facilities.

Nuclear safety and security are essential elements of radiation protection. Integration of nuclear safety and security provides a means to identify conflict and synergy points. Research has not been performed to enable integrated practices at the facility level. A tool was developed through research to help staff and regulators assess the level of integration practiced within a research reactor. This tool aims to improve the identification of synergistic and conflict points. Eight criteria of nuclear safety and security integration were used to create the integration assessment tool: access control, transportation, emergency response, proper disposal of materials, testing and maintenance, defense in depth, training and education, and culture. The tool's final score can range from 0.0375 to 1, with a score of 1 indicating complete integration. The tool was used by research reactor staff to assess practiced integrative techniques. The testing and maintenance criterion scored the highest level of integration (0.84). Training and education and culture scored the lowest levels of integration (0.50). The areas with the highest scores identified points of actively practiced integration. In contrast, those areas with lower scores indicated a lack of integrative practices. The total integration score was 0.69. This tool determined that the facility practiced an adequate level of integration. By analyzing integration levels with this tool, a measurable standard of integrative practices can be employed to achieve improved radiation protection.

Integrating LiDAR Sensor Data into Microsimulation Model Calibration for Proactive Safety Analysis.

Studies have shown that vehicle trajectory data are effective for calibrating microsimulation models. Light Detection and Ranging (LiDAR) technology offers high-resolution 3D data, allowing for detailed mapping of the surrounding environment, including road geometry, roadside infrastructures, and moving objects such as vehicles, cyclists, and pedestrians. Unlike other traditional methods of trajectory data collection, LiDAR's high-speed data processing, fine angular resolution, high measurement accuracy, and high performance in adverse weather and low-light conditions make it well suited for applications requiring real-time response, such as autonomous vehicles. This research presents a comprehensive framework for integrating LiDAR sensor data into simulation models and their accurate calibration strategies for proactive safety analysis. Vehicle trajectory data were extracted from LiDAR point clouds collected at six urban signalized intersections in Lubbock, Texas, in the USA. Each study intersection was modeled with PTV VISSIM and calibrated to replicate the observed field scenarios. The Directed Brute Force method was used to calibrate two car-following and two lane-change parameters of the Wiedemann 1999 model in VISSIM, resulting in an average accuracy of 92.7%. Rear-end conflicts extracted from the calibrated models combined with a ten-year historical crash dataset were fitted into a Negative Binomial (NB) model to estimate the model's parameters. In all the six intersections, rear-end conflict count is a statistically significant predictor (p-value < 0.05) of observed rear-end crash frequency. The outcome of this study provides a framework for the combined use of LiDAR-based vehicle trajectory data, microsimulation, and surrogate safety assessment tools to transportation professionals. This integration allows for more accurate and proactive safety evaluations, which are essential for designing safer transportation systems, effective traffic control strategies, and predicting future congestion problems.

A novel inherent safety index for reactive hazard evaluation integrating thermal and pressure effects

Chemical reactive hazard is one of the main causes for accidents in chemical production, inherent safety indexing methodology is considered the most effective method for reactive hazard evaluation. Traditional reactive inherent safety indices often neglect pressure-related risks in runaway scenarios. This work introduced a chemical reactive risk index (CRRI), filling the gap in pressure risk assessment. CRRI integrates a semi-quantitative method based on risk analysis principles, consisting of the probability of reaction runaway and the severity of its consequences. The consequence of the whole runaway process is evaluated, and the severity of thermal and pressure effects are considered comprehensively. The PVA, TBHP and PFA production processes are utilized as case studies to demonstrate the application process and evaluation effectiveness of CRRI. The results illustrate the superiority of CRRI in comprehensive assessment of reaction risks, indicating CRRI as a reliable safety assessment tool for chemical reactions, helping to select inherently safer reaction processes.

BiMPADR: A Deep Learning Framework for Predicting Adverse Drug Reactions in New Drugs.

Detecting the unintended adverse reactions of drugs (ADRs) is a crucial concern in pharmacological research. The experimental validation of drug-ADR associations often entails expensive and time-consuming investigations. Thus, a computational model to predict ADRs from known associations is essential for enhanced efficiency and cost-effectiveness. Here, we propose BiMPADR, a novel model that integrates drug gene expression into adverse reaction features using a message passing neural network on a bipartite graph of drugs and adverse reactions, leveraging publicly available data. By combining the computed adverse reaction features with the structural fingerprints of drugs, we predict the association between drugs and adverse reactions. Our models obtained high AUC (area under the receiver operating characteristic curve) values ranging from 0.861 to 0.907 in an external drug validation dataset under differential experiment conditions. The case study on multiple BET inhibitors also demonstrated the high accuracy of our predictions, and our model's exploration of potential adverse reactions for HWD-870 has contributed to its research and development for market approval. In summary, our method would provide a promising tool for ADR prediction and drug safety assessment in drug discovery and development.

Assessment tools in food safety and adherence to the sanitary protocol for coping with COVID-19 in food services

Food services, which must meet the sanitary standards for food production, needed to adapt to COVID-19 protocols in times of pandemic. In this context, the study of food safety assessment tools and sanitary protocols can contribute to the systematization of sanitary control actions and to the understanding how services have adapted to the new requirements. Thus, the present study aims to evaluate the relationships among the results of the assessment tools for food safety and adherence to the sanitary protocol for coping with COVID-19 in food services. Sanitary inspections were performed in 40 food services located in the center of the city of São Paulo – Brazil. Data were collected through the application of four checklists to evaluate the following: i. risk for FBD; ii. Good Handling Practices; iii. the structural requirements; and iv. The implementation of the COVID-19 sanitary protocol. The risk assessment tool was interpreted using a risk score, with each item weighted according to the risk for FBD. The results of the other tools were evaluated using the overall percentage of violated items. The results showed the predominance of high risk of GHP in the food services evaluated and a high percentage of violation of Good Handling Practices and structural requirements. The percentage of violation of the COVID-19 health protocol was moderate in most establishments. The degree of risk showed a high positive correlation with Good Handling Practices violations (Spearman ρ = 0.73; p < 0.001) and structural requirements (Spearman ρ = 0.63; p < 0.001). Regarding the tool for assessing adherence to the COVID-19 sanitary protocol, a moderate correlation was found with the violations of Good Handling Practices (Spearman ρ = 0.65; p < 0.001), with an emphasis on the thematic block relevant to food handlers. This discussion of the relationships among the results of the evaluation tools and their measurements may therefore be useful for improving the application of these tools by professionals involved in inspection activities, allowing the greater systematization of sanitary control actions and contributing to reduced risk of FBD.

Evaluation of medication safety assessment tools for pharmacist-led medication reviews: the Eastern European pilot project.

Background: Pharmacist-led medication reviews (MR) are one of the key methods to support medication safety in polypharmacy patients. The aims of this study were to pilot MRs in Eastern European community pharmacies, describe medication use in polypharmacy patients, and evaluate the usability of medication safety assessment tools. Methods: The MR pilot was undertaken in Estonia, Latvia, Poland, Hungary, Romania, and Bulgaria. Patients who used at least five medicines were directed to the service by their GPs. Data on drug-related problems (DRPs) and adherence were collected by pharmacists through structured patient interviews. Databases for identification of potential drug-drug interactions (pDDIs) and adverse drug reactions (ADRs) named Inxbase/Riskbase, as well as an integrated tool comprising potentially inappropriate medicines (PIMs) lists EU(7)-PIM and EURO-FORTA, were applied retroactively to the MR pilot data to investigate possibilities for their use and to describe medication use and potential risks in the study population. Results: A total of 318 patients were included in the study, 250 of them elderly (≥65 years). One hundred and eighty (56.6%) participants had a total of 504 pDDIs based on Inxbase analysis. On average, there were 1.6 pDDIs per participant. Twenty-five (5.0%) of the 504 pDDIs were in a high-risk category. A total of 279 (87.7%) participants had a potential ADR in at least one of 10 Riskbase categories. One hundred and fifty-four (20.8%) of the potential ADRs were in a high-risk category. Twenty-seven pDDIs and 68 ADRs documented as DRPs during the service were not included in the databases. Using the integrated EU(7)-PIM/EURO-FORTA PIM list, a total of 816 PIMs were found in 240 (96%) of the 250 elderly participants (on average 3.4 PIMs per elderly participant). Seventy-one (29.6%) of the participants were using high-risk PIMs. Twenty-one percent of high-risk PIMs and 13.8% of medium-risk PIMs were documented as DRPs by the pharmacists during the pilot. Conclusion: Medication safety assessment tools can be useful in guiding decision-making during MRs; however, these tools cannot replace patient interviews and monitoring. Tools that include a thorough explanation of the potential risks and are easy to use are more beneficial for MRs.

‘DANMM that’s good!’: evaluating the feasibility and acceptability of the Deadly Aboriginal and Torres Strait Islander Nursing and Midwifery Mentoring (DANMM) Programme across rural, regional and metropolitan NSW–a collaborative study protocol

IntroductionThis paper will describe the research protocol for the Deadly Aboriginal and Torres Strait Islander Nursing and Midwifery Mentoring (DANMM) Project, which will determine the feasibility and acceptability of a...

MtADENet: A novel interpretable method integrating multiple types of network-based inference approaches for prediction of adverse drug events

Identification of adverse drug events (ADEs) is crucial to reduce human health risks and accelerate drug safety assessment. ADEs are mainly caused by unintended interactions with primary or additional targets (off-targets). In this study, we proposed a novel interpretable method named mtADENet, which integrates multiple types of network-based inference approaches for ADE prediction. Different from phenotype-based methods, mtADENet introduced computational target profiles predicted by network-based methods to bridge the gap between chemical structures and ADEs, and hence can not only predict ADEs for drugs and novel compounds within or outside the drug-ADE association network, but also provide insights for the elucidation of molecular mechanisms of the ADEs caused by drugs. We constructed a series of network-based prediction models for 23 ADE categories. These models achieved high AUC values ranging from 0.865 to 0.942 in 10-fold cross validation. The best model further showed high performance on four external validation sets, which outperformed two previous network-based methods. To show the practical value of mtADENet, we performed case studies on developmental neurotoxicity and cardio-oncology, and over 50 % of predicted ADEs and targets for drugs and novel compounds were validated by literature. Moreover, mtADENet is freely available at our web server named NetInfer (http://lmmd.ecust.edu.cn/netinfer/). In summary, mtADENet would be a powerful tool for ADE prediction and drug safety assessment in drug discovery and development.

Visual Tools for Food Safety Assessment of Biotechnological Products

Food biotechnology, a revolutionary discipline, has transformed the way we produce, process and consume our food. It has enabled the development of new methods of crop genetic improvement, the creation of functional foods with health benefits, and the optimization of fermentation and food production processes. It has also provided innovative solutions to address the global challenges of food security and sustainability, while opening up new possibilities for nutrition and human health.

Applicability of 'Toolkit for Safety Assessment' tool to interventional radiology using probabilistic risk assessment techniques.

Interventional radiology brings extensive benefits to patients. Nevertheless, certain procedures may result in high doses of radiation, leading to health risks to occupationally exposed individuals (OEIs). Therefore, a more comprehensive risk analysis is essential to ensuring safety and minimising radiation exposures for all OEIs. The Toolkit for Safety Assessment (TOKSA) tool performs risk assessments based on the concepts described in 'General Safety Requirements' Part 3 (Radiation Protection and Safety of Radiation Sources: International Basic Safety Standards) and Part 4 (Safety Assessment for Facilities and Activities). This tool was developed based on the 'Ibero-American Forum of Radiological and Nuclear Regulatory Agencies' risk models and can promote the use of the risk assessment processes by OEIs. The aim of this study was to experimentally analyse the applicability of the TOKSA tool in interventional radiology with the use/support of probabilistic risk assessment techniques. The results were used to reduce the risks associated with a hemodynamics room in a hospital in Belo Horizonte, Brazil.

Multimodal Deep Neural Network-Based Sensor Data Anomaly Diagnosis Method for Structural Health Monitoring

Due to sensor failure, noise interference and other factors, the data collected in the structural health monitoring (SHM) system will show a variety of abnormal patterns, which will bring great uncertainty to the structural safety assessment. This paper proposes an automatic data anomaly diagnosis method for SHM based on a multimodal deep neural network. In order to improve the detection accuracy, both two-dimensional and one-dimensional features of the sensor data are fused in the multimodal deep neural network. The network consists of two convolutional neural network (CNN) channels, one a 2D-CNN channel for extracting time–frequency features of sensor data and the other a 1D-CNN channel for extracting raw one-dimensional features of sensor data. After convolution and pooling operations for the sensor data by the 2D channel and 1D channel separately, the two types of extracted features are flattened into one-dimensional vectors and concatenated at the concatenation layer. The concatenated vector is then fed into fully connected layers for final SHM data anomaly classification. In order to evaluate the reliability of the proposed method, the monitored data lasting for one month of a long-span cable-stayed bridge were used for training, validation, and testing. Six types of training conditions (missing, minor, outlier, over-range oscillation, trend, and drift) are studied and analyzed to address the issue of imbalanced training data. With an accuracy rate of 95.10%, the optimal model demonstrates the effectiveness and capability of the proposed method. The proposed method shows a promising future as a reliable AI-assisted digital tool for safety assessment in structural health monitoring systems.

Profiling alveolar macrophage responses to inhaled compounds using in vitro high content image analysis

One of the main hurdles in the development of new inhaled medicines is the frequent observation of foamy macrophage (FM) responses in non-clinical studies in experimental animals, which raises safety concerns and hinders progress into clinical trials. We have investigated the potential of a novel multi-parameter high content image analysis (HCIA) assay as an in vitro safety screening tool to predict drug induced FM.Rat (NR8383) and human U937-derived alveolar macrophages were exposed in vitro to a panel of model compounds with different biological activity, including inhaled bronchodilators, inhaled corticosteroids (ICS), phospholipidosis inducers and proapoptotic agents. An HCIA was utilized to produce drug-induced cell response profiles based on individual cell health, morphology and lipid content parameters.The profiles of both rat and human macrophage cell lines differentiated between cell responses to marketed inhaled drugs and compounds known to induce phospholipidosis and apoptosis. Hierarchical clustering of the aggregated data allowed identification of distinct cell profiles in response to exposure to phospholipidosis and apoptosis inducers. Additionally, in NR8383 cell responses formed two distinct clusters, associated with increased vacuolation with or without lipid accumulation. U937 cells presented a similar trend but appeared less sensitive to drug exposure and presented a narrower range of responses.These results indicate that our multi-parameter HCIA assay is suitable to generate characteristic drug-induced macrophage response profiles, thus enabling differentiation of foamy macrophage phenotypes associated with phospholipidosis and apoptosis. This approach shows great potential as pre-clinical in vitro screening tool for safety assessment of candidate inhaled medicines.

Proteomics coupled with AhR-reporter gene bioassay for human and environmental safety assessment of sewage sludge and hydrochar

Today application of sewage sludge (SL) and hydrochar (HC) in agriculture is a common practice for soil conditioning and crop fertilization, however safety concerns for human and environmental health due to the presence of toxic compounds have recently been expressed.Our aim was to test the suitability of proteomics coupled with bioanalytical tools for unravelling mixture effects of these applications in human and environmental safety assessment. We conducted proteomic and bioinformatic analysis of cell cultures used in the DR-CALUX® bioassay to identify proteins differentially abundant after exposure to SL and the corresponding HC, rather than only using the Bioanalytical Toxicity Equivalents (BEQs) obtained by DR-CALUX®.DR-CALUX® cells exposed to SL or HC showed a differential pattern of protein abundance depending on the type of SL and HC extract. The modified proteins are involved in antioxidant pathways, unfolded protein response and DNA damage that have close correlations with the effects of dioxin on biological systems and with onset of cancer and neurological disorders. Other cell response evidence suggested enrichment of heavy metals in the extracts.The present combined approach represents an advance in the application of bioanalytical tools for safety assessment of complex mixtures such as SL and HC. It proved successful in screening proteins, the abundance of which is determined by SL and HC and by the biological activity of legacy toxic compounds, including organohalogens.

An operational risk awareness tool for small fishing vessels operating in harsh environment

Probabilistic safety assessment using the Bayesian network (BN) has emerged as a popular method for developing risk analysis tools. The method allows for risk-influencing factors from several areas to be captured probabilistically, enabling an easy-to-use safety assessment tool to be developed. Meanwhile, because the resulting tool is a BN model, the use of subject-matter experts in eliciting probabilities for the conditional probability tables (CPT) makes the method subjective. The subjectivity makes the tool's output result less reliable since different experts rarely produce the same probabilities for CPTs. Therefore, the present study proposed a probability-scoring scale that uses pre-determined scores to assign probabilities to CPTs. Using the scale ensures that different experts working on a common CPT produce identical probabilities. That way, the variability among experts’ results is minimised while the reliability of a BN's output result increases. The scale was applied to a BN-based risk-awareness (RAw) tool developed for monitoring safety aboard small fishing vessels (SFV). Advanced safety monitoring equipment is lacking aboard many SFVs, especially those in developing countries. Hence, the RAw tool developed in the present study demonstrates how the probabilistic safety assessment method could be leveraged to equip SFVs with safety monitoring tools. The study will benefit SFV owners and operators, the commercial fishing industry, and maritime administrations in charge of ensuring safety aboard SFVs.

Reconstructed human intestinal comet assay, a possible alternative in vitro model for genotoxicity assessment.

The aim of the present study was to evaluate the compatibility of reconstructed 3D human small intestinal microtissues to perform the in vitro comet assay. The comet assay is a common follow-up genotoxicity test to confirm or supplement other genotoxicity data. Technically, it can be performed utilizing a range of in vitro and in vivo assay systems. Here, we have developed a new reconstructed human intestinal comet (RICom) assay protocol for the assessment of orally ingested materials. The human intestine is a major site of food digestion and adsorption, first-pass metabolism as well as an early site of toxicant first contact and thus is a key site for evaluation. Reconstructed intestinal tissues were dosed with eight test chemicals: ethyl methanesulfonate (EMS), ethyl nitrosourea (ENU), phenformin hydrochloride (Phen HCl), benzo[a]pyrene (BaP), 1,2-dimethylhydrazine hydrochloride (DMH), potassium bromate (KBr), glycidamide (GA), and etoposide (Etop) over a span of 48 h. The RICom assay correctly identified the genotoxicity of EMS, ENU, KBr, and GA. Phen HCl, a known non-genotoxin, did not induce DNA damage in the 3D reconstructed intestinal tissues whilst showing high cytotoxicity as assessed by the assay. The 3D reconstructed intestinal tissues possess sufficient metabolic competency for the successful detection of genotoxicity elicited by BaP, without the use of an exogenous metabolic system. In contrast, DMH, a chemical that requires liver metabolism to exert genotoxicity, did not induce detectable DNA damage in the 3D reconstructed intestinal tissue system. The genotoxicity of Etop, which is dependent on cellular proliferation, was also undetectable. These results suggest the RICom assay protocol is a promising tool for further investigation and safety assessment of novel ingested materials. We recommend that further work will broaden the scope of the 3D reconstructed intestinal tissue comet assay and facilitate broader analyses of genotoxic compounds having more varied modes of actions.