Safety Systems Research Articles

Development of PHM Algorithm of e-Latch to Prepare for the Era of Autonomous Driving

In self-driving vehicles linked with mobility electrification, system failures that occur suddenly in situations where customers are unaware of signs of failure are directly related to customer injuries. Securing the durability and safety of closure automation system is necessary to increase the customer's safety value so PHM technology makes it possible to predict failures and remaining life in advance during system operation. In addition, since not only various forms of new concept design styling but also innovative new handle designs are applied, it is obviously seen that e-Latch system is widely equipped in the mobility. Thus, in this paper, the study to predict the failure of e-Latch and closure system is implemented via data-driven and physics-driven method, and the algorithm for PHM to estimate remaining life of e-Latch system is also introduced.

Enhancing Perioperative Outcomes of Pancreatic Surgery with Wearable Augmented Reality Assistance System: A Matched-Pair Analysis

Objective: The present study aimed to evaluate the safety of the first wearable augmented reality assistance system (ARAS) specifically designed for pancreatic surgery and its impact on perioperative outcomes. Background: Pancreatic surgery remains highly complex and is associated with a high rate of perioperative complications. ARAS, as an intraoperative assistance system, has the potential to reduce these complications. Methods: This prospective, single-center study included 20 patients who underwent pancreatic surgery using ARAS. These patients were matched in a 1:3 ratio with 60 patients from our retrospective data who underwent standard pancreatic resection. Matching variables were selected based on factors associated with poor intraoperative outcomes. Results: A higher proportion of patients in the ARAS group were diagnosed with borderline resectable pancreatic cancer and received neoadjuvant chemotherapy (20.0% vs 6.7%, P = 0.085). Additionally, more patients in the ARAS group required arterial resection compared with the control group (15.0% vs 0.0%, P = 0.002). Nevertheless, the ARAS group had a significantly shorter operative time (246 vs 299 minutes, P = 0.004) and required significantly fewer intraoperative blood transfusions (0.0 ± 0.0 vs 0.5 ± 1.4 units, P = 0.014). None of the patients in the ARAS group had positive resection margins (0.0% vs 20.0%, P = 0.045). Furthermore, patients in the ARAS group experienced a significantly shorter hospital stay (13.8 ± 6.6 vs 17.9 ± 8.2 days, P = 0.046). Conclusions: ARAS is a safe and effective assistance system for pancreatic surgery, offering superior perioperative outcomes compared with standard procedures.

Video WeAther RecoGnition (VARG): An Intensity-Labeled Video Weather Recognition Dataset

Adverse weather (rain, snow, and fog) can negatively impact computer vision tasks by introducing noise in sensor data; therefore, it is essential to recognize weather conditions for building safe and robust autonomous systems in the agricultural and autonomous driving/drone sectors. The performance degradation in computer vision tasks due to adverse weather depends on the type of weather and the intensity, which influences the amount of noise in sensor data. However, existing weather recognition datasets often lack intensity labels, limiting their effectiveness. To address this limitation, we present VARG, a novel video-based weather recognition dataset with weather intensity labels. The dataset comprises a diverse set of short video sequences collected from various social media platforms and videos recorded by the authors, processed into usable clips, and categorized into three major weather categories, rain, fog, and snow, with three intensity classes: absent/no, moderate, and high. The dataset contains 6742 annotated clips from 1079 videos, with the training set containing 5159 clips and the test set containing 1583 clips. Two sets of annotations are provided for training, the first set to train the models as a multi-label weather intensity classifier and the second set to train the models as a multi-class classifier for three weather scenarios. This paper describes the dataset characteristics and presents an evaluation study using several deep learning-based video recognition approaches for weather intensity prediction.

Analysis of Children's Road Crashes in Hungary

In the EU, more than 6,000 children died in road accidents between 2011 and 2020. Children are particularly vulnerable road users, and they need to be protected. This underlines the importance of the Safe System approach. The Safe System approach is a holistic view of road safety, which integrates the different elements of the traffic system and takes human vulnerability and fallibility into account. Children are still in the phase of developing the cognitive and physical skills necessary to travel safely in traffic. Because of their small size, children are less visible than other road users and less experienced; they can easily become innocent victims in collisions. Despite significant improvements in vehicle safety in recent years, almost half of all child road deaths occur while traveling in cars. Limited data is available on the correct use of child seats in cars across the EU, but studies have shown that misuse remains a significant problem. Several measures have been taken in recent years to make it safer for children to travel on the roads, but many more interventions are needed to further improve their safety. Our research aimed to examine the characteristics of child accidents in Hungary and to highlight the main road safety problems affecting children in Hungary.

Large Eddy Simulation of large-scale hydrogen deflagrations using the Thickened Flame Model with stretch sensitivity adaptation and thermo-diffusive instability modeling

Due to the high costs associated to experimental testing of hydrogen (H2) explosions, numerical simulations play an essential role in the design of safe industrial systems. In this work, we investigate the use of the Thickened Flame Model (TFM) to perform simulations of H2 deflagrations. Specific issues arise when considering hydrogen: (i) due to differential diffusion, the flame is very sensitive to stretch; (ii) instabilities of the flame front are generated and lead to an increased flame propagation speed. Both of these phenomena are affected by flame thickening. First, the flame sensitivity to stretch is artificially increased by the thickening. The recently developed Ma-TFM model proposes a correction of diffusive fluxes to reach the correct Markstein length and is selected in this work. Secondly, thermo-diffusive and hydrodynamic flame instabilities are also altered by thickening. By computing the dispersion relationship for a hydrogen/air mixture, we show that the instability scales are proportional to the thickening factor F. A simple subgrid scale (SGS) model, based on the computations of laminar unstable 2-D and 3-D flames, is then considered to take into account the effect of instabilities. The Ma-TFM and SGS instability models are applied together for the first time on a semi-industrial vented lean hydrogen deflagration, leading to promising results. In particular, it is found that considering 3-D unstable flames is necessary to accurately predict the experimental pressure peaks.

Photo-fenton catalysis degradation of 4-dodecylmorpholine by heterogeneous microprocessor Cu2O/SnO2

The increasing demand for potash has led to the increased use of 4-dodecyl morpholine (DMP), an important froth flotation agent for the extraction for potash extraction by “reverse flotation-cold crystallization”. As it is not easy to be stable and decompose in its natural state, it has seriously endangered the environment of salt lakes and the development of salt lake resources. The development of a safe and harmless catalytic system to accomplish the degradation and removal of DMP is urgent. Herein, A Cu2O/SnO2/PDA (CSP) nanoparticle with a synergistic effect of photocatalysis and Fenton-like catalysis was developed, and the CSP had a good photothermal conversion efficiency. Under 808 nm NIR irradiation, not only the catalyst activity was enhanced, but also the complexation rate of electron-hole pairs was reduced, which effectively increased the degradation efficiency of DMP (an increase of about 31.56 %). In addition, by analyzing the degradation products of DMP, the possible pathways of the DMP degradation process were proposed and, at the same time, the degradation catalytic system we used was proved to be safe and harmless. A new pathway is provided for the degradation and removal of DMP in the salt lake environment.

A Novel Delivery System for the Combined Use of Natural Ingredients: The Preparation of Berberine Hydrochloride-Matrine Liposomes and Preliminary Exploration of Their Anti-Tumor Activity.

Berberine hydrochloride (BH) extracted from Coptis chinensis (CC) and Matrine (MT) separated from Sophora flavescens (SF) are alkaloids with potent anti-bacterial, anti-inflammatory, and anti-tumor effects. Motivated by the clinical practice of using CC and SF together, we aimed to demonstrate that the synergistic application of the natural compounds BH and MT could enhance therapeutic effects and minimize side effects. Two types of liposomes, liposomes containing only BH (BH-LP) and liposomes containing both BH and MT (BH-MT-LP), were successfully prepared via the reverse evaporation method. The liposome preparation process was optimized by single-factor screening and the Box-Behnken experimental design method. The results showed that the liposomes had particle sizes in the range of 222.7 to 235.4 nm, polydispersity indicated in the range of 11.8% to 23.3%, and zeta potentials in the range of -35.9 to -31.1 mv. BH-MT-LP showed superior anti-tumor activity against MDA-MB-231, HepG-2, and HGC-27 cells in vitro. The incorporation of MT effectively promoted the anti-tumor effect of BH, while the controlled release from liposomes further enhanced the therapeutic efficacy of BH. Furthermore, based on the flow cytometry results, we speculated that BH-MT-LP might promote apoptosis by blocking the G1 phase of cells and inducing cell death. In conclusion, BH-MT-LP provides evidence for the combined use of natural compounds as a stable, safe, and practical drug delivery system for the treatment of potential cancers. Meanwhile, the successful preparation for BH-MT-LP also provides a new approach to the combined use of traditional Chinese medicine ingredients.

In Situ Transformable Fibrillar Clusters Disrupt Intracellular Copper Metabolic Homeostasis by Comprehensive Blockage of Cuprous Ions Efflux.

Dysregulation of copper metabolism is intricately associated with the occurrence and therapeutic management of colorectal cancer. Previous studies have attempted to induce cuproptosis by delivering lethal doses of copper ions into tumor cells, often with systemic safety risks. In vivo, transformable peptide is modular and designed for various tumor-related proteins, which can affect protein function and distribution. Here, a fibrillar transformation peptidic (FTP) nanoparticle is synthesized, which can bind ATP7B membrane proteins (cuprous ions transporter) and transform into nanofibrils/ATP7B clusters, inducing "copper-free cuproptosis" in vivo. Without adding exogenous copper ions, the spherical FTP nanoparticles bound the high distribution regions of ATP7B membrane proteins, transforming into fibrillar networks in situ with prolonged retention. The cage-like fibrillar network would further capture unbound or newly generated free ATP7B membrane proteins, thereby significantly and consistently preventing cuprous ions efflux. The FTP nanoparticles would not undergo in situ fibrillar transformation on the low expression region of ATP7B membrane proteins but enter the cell for safe degradation, which exhibited high specificity and safety in vivo. By disrupting intracellular copper homeostasis, the transformable fibrillar clusters displayed a long-term anti-tumor effect on subcutaneous transplantation and liver metastatic CRC models.

A new portable negative pressure wound therapy device: a prospective study investigating clinical outcomes.

Closed surgical incision sites at high risk of complications, and with exudate or leakage, are increasingly being managed with closed incision negative pressure wound therapy (ciNPWT) to reduce tissue stress and increase the force necessary to disrupt the incision. This study was undertaken to investigate the performance and safety of a canister-based, single-use NPWT (suNPWT) system when used on closed surgical incision sites. The investigation was designed as a prospective, open, non-comparative, multicentre study aimed at confirming the safety and performance attributes of the suNPWT system when applied to low-to-moderately exuding closed surgical incisions. The primary performance measure was the wound remaining closed from baseline to the last follow-up visit on day 14. Secondary performance measures included: wound and periwound condition; wear time of the system; product consumption; adherence to therapy; and patients' pain progress. Details of adverse events were also collected. Some 35 patients were recruited. The closed surgical incisions responded well to treatment with the tested suNPWT system. All wounds remained closed throughout the investigation. Consistent with other studies of ciNPWT reporting low infection rates, the current study observed either no or low exudation in 90.4% of wounds at the final visit, together with absence of surgical site infection. Pain severity levels were low, both at dressing change and during delivery of negative pressure. No serious adverse device events were reported. In this study, the suNPWT system supported the healing of closed surgical incisions with no safety concerns relating to its use.

Optimization of chemical engineering control for large-scale alkaline electrolysis systems based on renewable energy sources

In the context of renewable energy, dynamic control is crucial for large-scale alkaline water electrolysis systems. Under traditional Proportional-Integral-Derivative (PID) control, the system's temperature and impurity levels may exceed safe limits during sudden load changes, compromising system safety. Therefore, this study proposes a control strategy based on mathematical models of system temperature and impurities, including Model Predictive Control (MPC) for temperature and Optimal Curve Tracking (OCT) for impurities. The MPC controller offsets the disturbances in temperature caused by current fluctuations through state prediction, while the OCT controller ensures that impurity levels remain within safe limits. Real-time application of these control strategies is achieved through MATLAB-PLC communication, validating controller performance. Experimental results show that the MPC controller exhibits excellent dynamic response and stability in controlling the stack temperature, with a maximum temperature peak deviation of only 2.9 K and a temperature fluctuation range of 5.9 K. This represents a reduction of 1.6 K in peak deviation compared to traditional PID controllers and significantly decreases the temperature fluctuation range. The OCT controller also demonstrates good safety and stability in controlling hydrogen to oxygen (HTO) impurity levels, consistently maintaining the HTO content at the set upper limit of 1.5%, thereby expanding the safe operational range of the system and reducing the need for frequent adjustments to the system setpoints.

Application of systems safety principles for O&M of floating offshore wind

Abstract The offshore wind industry is growing rapidly and is also a high risk industry with unique safety challenges. As the industry grows, more research is needed to make sure it operates safely and provides a workplace in which all involved can go home free of injury. The adoption of floating wind turbines brings new hazards and increased complexity to offshore wind operations and maintenance. Floating wind operations will involve the development of new deepwater sites and require the adoption of new strategies such as floating to floating transfers and towing operations. As the complexity of offshore operations increases it is important that the understanding of the hazards involved are developed. Floating wind is a new branch of the offshore wind industry and as technologies and systems have yet to become established there is the opportunity to do things differently and embed safety improvements in the industry from the outset. This study has looked at the potential application of systems safety theories to floating wind operations and maintenance. The application of systems engineering to improve safety performance has been growing across many industries in recent years. Systems safety considers that safety is an emergent property of a complex system that is a result of many interacting factors. This study looks at how systems safety could be applied to the emerging floating wind industry to build safety into the industry at the earliest stages. This study reviewed the applications of systems safety across similar industries and the offshore wind industry. It then looks at existing hazards of floating wind that have already been identified in the literature and completed a systems theory hazard analysis of floating wind O&M activities. This involved the mapping of the safety control structure for floating wind operations and the identification of potential gaps between the safety controls and safety requirements. It then explores how systems safety processes could be applied to floating wind and makes recommendations for how these could be implemented to the emergent industry. The study found existing research of systems safety applied to the offshore wind industry is currently very limited. Its application has been successful in similar industries and there is potential for a systems safety approach to be used in the development of floating wind operations and maintenance. The systems theory hazard analysis can help identify potential systemic risks arising as a result of the interaction of multiple systems. It can be used to develop appropriate control structures to manage safety and could also be used for the identification of leading indicators to manage safety performance.

Failure effects analysis on safety properties for hard logic in reactor protection system using model checking

Ensuring the reliability and safety of safety-critical systems within nuclear power plant hinges upon efficient failure effects analysis. Conventional approaches to failure effects analysis in reactor protection systems encounter notable challenges, including labor-intensive manual analysis and limitations in ensuring comprehensive analysis coverage. To tackle these issues head-on, we introduce a novel methodology termed Failure Effects Analysis on Safety Properties (FEA-SP). Grounded in model checking technology, this method facilitates automated failure analysis processes. By harnessing the exhaustive state space exploration capabilities inherent in model checking, the FEA-SP methodology adopts the safety properties of the system as its granularity and verification focal point. A detailed component-level case study involving a hard logic within the HPR1000 nuclear reactor protection system underscores the efficacy and practicality of the proposed approach, especially in the thorough examination of system spurious actions. The failure effects analysis method delineated in this paper holds broad applicability and serves as a valuable reference for the analysis of failure effects in safety systems.

Novel versus Established Cryoballoon Ablation System for Atrial fibrillation: A Systematic Review and Meta-Analysis

BackgroundRecently a novel cryoballoon ablation (CBA) system (POLARx) for the treatment of atrial fibrillation (AF) has been introduced. ObjectiveWe aimed at systematically reviewing the efficacy and safety of the POLARx to the ArcticFront system. MethodsStructured systematic database search for articles published between 2021 and 2024 reporting the efficacy and/or safety of the POLARx system for AF ablation. The co-primary endpoints were the long-term efficacy and safety of the POLARx system ResultsOf the 24 studies with 5364 patients (weighted mean age 62.4 years) included, 15 compared the POLARx system (1746 patients) to the ArcticFront system (2282 patients). Despite significantly lower temperatures at isolation (POLARx -46.3°C, ArcticFront -31.6°C, p <0.01) and nadir temperatures (POLARx -56.5°C ArcticFront -47.8°C p <0.01), the POLARx system did not show a better acute (98.9% and 99.2% successfully ablated patients, 99.5% and 99.8% successfully ablated pulmonary veins in the POLARx and ArcticFront group, respectively) or long-term efficacy (After a weighted mean follow-up of 12.6 months, the success rate was 69.5% with POLARx and 60.2% with ArcticFront (p = 0.98)). While most complications were similar between the POLARx and ArcticFront group, the incidence of phrenic nerve palsies in the pooled cohorts (all POLARx vs all ArcticFront control patients) differed (2.7% vs. 1.6% in the POLARx vs. ArcticFront group, respectively, OR 1.79 [1.14-2.83], p-value = 0.01). ConclusionThe novel POLARx system provided similar efficiency and acute/long-term efficacy, but showed a higher incidence of phrenic nerve palsies compared to the ArcticFront system.

A hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power system. The data-driven forecasting methods are regarded as an effective solution. However, the inherent randomness and nonlinearity of wind power systems, along with the abundance of redundant information in measurement data, present challenges to forecasting methods. The integration of precise and efficient techniques for data feature decomposition and extraction is essential in conjunction with advanced data-driven forecasting models. Focus on the seasonal variation characteristics of wind energy, a hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction is proposed. The effectiveness and superiority of the proposed method in predictive accuracy are demonstrated through comprehensive multi-model experiment comparisons.

Design strategies of polysaccharide, protein and lipid-based nano-delivery systems in improving the bioavailability of polyphenols and regulating gut homeostasis.

Polyphenols are plant secondary metabolites that have attracted much attention due to their anti-inflammatory, antioxidant, and gut homeostasis promoting effects. However, food matrix interaction, poor solubility, and strong digestion and metabolism of polyphenols cause barriers to their absorption in the gastrointestinal tract, which further reduces bioavailability and limits polyphenols' application in the food industry. Nano-delivery systems composed of biocompatible macromolecules (polysaccharides, proteins and lipids) are an effective way to improve the bioavailability of polyphenols. Therefore, this review introduces the construction of biopolymer-based nano-delivery systems and their application in polyphenols, with emphasis on improving the solubility, stability, sustained release and intestinal targeting of polyphenols. In addition, there are possible positive effects of polyphenol-loaded nano-delivery systems on modulating gut microbiota and gut homeostasis, with particular emphasis on modulating intestinal inflammation, metabolic syndrome, and gut-brain axis. It is worth noting that the safety of bio-based nano-delivery systems still need to be further studied. In summary, the application of the bio-based nano-delivery system to deliver polyphenols provides insights for improving the bioavailability of polyphenols and for the treatment of potential diseases in the future.

Evaluating efficacy and safety of a novel registration-free CT-guided needle biopsy navigation system (RC 120): A multicenter, prospective clinical trial

Evaluating efficacy and safety of a novel registration-free CT-guided needle biopsy navigation system (RC 120): A multicenter, prospective clinical trial

The Food and Drug Administration’s Safety Surveillance of Adverse Event Cases Involving Cannabinoid Hemp Products, 2019–2023

Objective. To characterize adverse event (AE) cases received by the US Food and Drug Administration (FDA) reportedly involving cannabinoid hemp products (CHPs). Methods. We searched the FDA Adverse Event Reporting System and Center for Food Safety and Applied Nutrition Adverse Event Reporting System for cases reported directly to the FDA from 2019–2023 involving CHPs, which are defined as products containing 1 or more of the following: cannabidiol, delta-8 tetrahydrocannabinol, and emerging cannabinoids (i.e., other intoxicating cannabinoids often synthesized from hemp-derived cannabidiol). We abstracted and summarized information on reporting trends, consumer demographics, reporter information, product information, and AEs. Results. We identified 610 AE cases reportedly involving CHPs containing 1 or more of the following: delta-8 tetrahydrocannabinol (n=355), cannabidiol (n=253), and emerging cannabinoids (n=36). Multiple trends and safety issues were identified, including an annual increase in the number of cases involving intoxicating cannabinoids since 2021, potential quality issues, and the occurrence of fatalities and pediatric exposures. Conclusions. Our findings emphasize the importance of monitoring AE cases received by the FDA involving CHPs as part of a comprehensive surveillance strategy to identify trends and safety issues with these products. ( Am J Public Health. 2024;114(S8):S664–S672. https://doi.org/10.2105/AJPH.2024.307712 )

CANBERRA, A Phase 2 Randomized Clinical Trial to Test the Therapeutic Potential of Oral Vicasinabin in Diabetic Retinopathy

ObjectiveNon-proliferative diabetic retinopathy (NPDR) is a progressive disease that can lead to blindness. Current therapies for NPDR are invasive and not extensively used or accessible until the disease progresses, pointing to the need for an early non-invasive treatment.The objective of CANBERRA was to assess the safety, tolerability, and efficacy of oral administration of vicasinabin (RG7774) on the severity of diabetic retinopathy (DR) in participants with moderately severe to severe NPDR and good vision. DesignCANBERRA was a global, multicentric randomized, double-masked, parallel-group, placebo-controlled, phase 2 study. The study duration was 36 months. 139 treatment-naïve participants with type 1 or type 2 diabetes mellitus and Diabetic Retinopathy Severity Scale (DRSS) levels of 47 or 53 in at least one eye. Eligible participants were randomized 1:1:1 to 36 weeks of daily oral placebo, vicasinabin 30mg, or vicasinabin 200mg. Participants were followed for an additional 12 weeks. Main OutcomeThe primary safety objective was to evaluate the safety and tolerability of vicasinabin by the frequency and severity of adverse events. The primary efficacy objective was to assess the effect of vicasinabin on the severity of DR, assessing the proportion of participants with at least 2-steps improvement in DRSS from baseline at week 36 in the study eye. ResultsResults are presented in the following order: placebo, vicasinabin 30mg, vicasinabin 200mg. 47, 48, and 44 participants were enrolled. Baseline characteristics were balanced. Adherence to treatment was approximately 90%, and pharmacokinetic analysis showed dose-dependent plasma exposure to vicasinabin. The primary efficacy endpoint was not met: the percentage of participants who improved their DRSS by at least two steps at week 36 from baseline were 7.9, 9.5, and 5.7, without statistically significant differences. The systemic and ocular safety profiles of vicasinabin were favorable, and adverse events distributed evenly across arms. Vicasinabin did not induce changes in glycemic control or any kidney function or cardiovascular parameters. Three patients in the placebo arm discontinued the study due to serious adverse events ConclusionsAt the doses tested, vicasinabin did not improve DRSS in participants with NPDR. The role of the cannabinoid system in diabetic retinopathy remains elusive

Traffic Prevention and Security Enhancement in VANET Using Deep Learning With Trusted Routing Aided Blockchain Technology

ABSTRACTVehicular ad hoc networks (VANETs) in portable broadband networks are a revolutionary concept with enormous potential for developing safe and efficient transportation systems. Because VANETs are open networks that require regular information sharing, it might be difficult to ensure the security of data delivered through VANETs as well as driver privacy. This paper proposes a blockchain technology that supports trusted routing and deep learning for traffic prevention and security enhancement in VANETs. Initially, the proposed Feature Attention‐based Extended Convolutional Capsule Network (FA_ECCN) model predicts the driver's behaviors such as normal, drowsy, distracted, fatigued, aggressive, and impaired. Next, the Binary Fire Hawks‐based Optimized Link State Routing Protocol (BFH_OLSRP) is used to route traffic after trust values have been assessed. Furthermore, Binary Fire Hawks Optimization (BFHO) determines the best routing path based on criteria such as link stability and node stability degree. Finally, blockchain storage is supported by the Interplanetary File System (IPFS) technology to improve the security of VANET data. Additionally, the validation process is established by using Delegated Practical Byzantine Fault Tolerance (DPBFT). As a result, the proposed study employs the blockchain system to securely send data to neighboring vehicles via trust‐based routing, thereby accurately predicting the driver's behavior. The proposed method achieves a better outcome in terms of latency, packet delivery ratio (PDR), overhead packets, throughputs, end‐to‐end delay, transmission overhead, and computational cost. According to simulation results and efficiency evaluation, the proposed approach outperforms existing approaches and enhances vehicle communication security in an effective manner.

Kind, Firm, and Fair Medical Regulation: A Systems Approach and Six Ethical Principles

ABSTRACT Background: Regulatory processes can be stressful, anxiety provoking, and complicated for the health professional involved, the institutions they work for, and for the regulators. Methods: This paper uses a case study to describe a systems approach to comprehensively identify the agents (ie: the complainant, the health professional concerned, the regulator dedicated to the case, the institution, the healthcare profession, the public, and the regulatory authority) and 6 ethical issues that emerge during the regulatory process: potential to cause harm, not in the best interest of a person, affects autonomy, unjust, not truthful, and loss of trust. Results: A systems approach lends to a mental model in which there are dynamic interactions across these elements accompanied by positive and negative feedback loops that maintain overall stability of the whole system. Conclusions: The process can be further refined and kinder to those concerned by developing a sensitive approach to improve assessment of risks, using feedback to improve the regulatory process, adapting transparent procedures, not causing undue delays to the process, embedding regulatory activities in a patient safety system, minimizing individual blame, using non-legalistic, non-threatening and respectful communications, and directing the different actors to a support network for guidance and advice.