Level Of Risk Research Articles

Driving factors and spatio-temporal evolution of tourist accident clusters in Chinese outbound tourism

ABSTRACT The clustering of tourist accidents is a critical yet underexplored area of research. This study employs cluster theory and safety system theory to develop a comprehensive measurement tool for analysing tourist accident clusters, examining their spatiotemporal evolution patterns, and identifying the driving mechanisms from a holistic destination perspective. By analysing accident records of Chinese outbound tourists across 48 countries from 2011 to 2019, the findings reveal a reduction in disparities among tourist accident clusters (α-convergence effect) and a fluctuating trend over time. Spatial autocorrelation analysis identifies four distinct spatial distribution patterns: low-low (L-L), high-low (H-L), high-high (H-H), and low-high (L-H). Furthermore, Boosted Regression Tree (BRT) analysis uncovers a nonlinear relationship between accident clusters and four primary factors: human, machine, environment, and management. Within this framework, indicators such as tourist volume pressure, traffic risk, and employee training levels emerge as significant contributors. Additionally, geographic detector analysis reveals interactions among the driving mechanisms, offering deeper insights into their interrelated effects. This study provides practical implications for destinations, tourists, and tourism practitioners, emphasising strategies to prevent and mitigate the impact of accident clusters.

Incidental nanoparticle characterisation in industrial settings to support risk assessment modelling.

Research on nanoparticle (NP) release and potential exposure can be assessed through experimental field campaigns, laboratory simulations, and prediction models. However, risk assessment models are typically designed for manufactured NP (MNP) and have not been adapted for incidental NP (INP) properties. A notable research gap is identifying NP sources and their chemical, physical, and toxicological properties, especially in real-world settings. This work aims to provide insights into the release and physico-chemical properties of INP while contributing to improving models for INP release. INP release was evaluated through a case study in a ceramic tile firing facility, where aerosol (10nm - 10μm) properties were determined. The Control Banding (CB) Nanotool model was applied to test outputs based on provided input parameters. RESULTS: demonstrate the constant generation and release of INP during tile firing, with NP concentrations up to 68711/cm³ and mean diameters of 37nm, with 95% smaller than 100nm. Particle morphology was mostly spherical, suggesting nucleation from precursor gases as the main formation mechanism. INP chemical composition was driven by primary ceramic components, while trace elements like Ni and Ti exhibited size-dependent patterns. In vitro cell viability tests indicated low to medium cytotoxicity of PM2 aerosols, decreasing human alveolar epithelial cell viability in a concentration-dependent manner. Applying the risk model with varying input parameters revealed that the risk level (RL) based on severity scores decreased when aerosol size distribution data were used, illustrating the model's sensitivity to input variables. We conclude on the need for comprehensive experimental datasets to support risk assessment models and achieve effective risk management strategies in real-world scenarios.

Incidence of Adrenal Insufficiency in Patients with High-Risk Neuroblastoma: A Single-Institution Analysis.

Neuroblastoma is the most common extracranial solid tumor in children, with about half of cases classified as high risk. Treatment varies by risk level, with high-risk patients undergoing aggressive multimodal therapy. While long-term survival has improved, survivors face significant risks of late treatment effects, including adrenal insufficiency. This study investigates the incidence of adrenal insufficiency among neuroblastoma patients of varying disease risk. This retrospective cohort study at a single tertiary children's hospital reviewed records from 1998 to 2021, identifying 370 neuroblastoma patients, with 137 having complete risk stratification. The primary outcome was the incidence of adrenal insufficiency, diagnosed via clinical evaluation, and compared by risk group. Among 137 patients with neuroblastoma, nine (12.0%) high-risk and three (4.9%) non-high-risk patients were diagnosed with adrenal insufficiency. The cumulative incidence of adrenal insufficiency at 3years after neuroblastoma diagnosis was 9.9% in high-risk and 3.5% in non-high-risk patients. Among high-risk neuroblastoma patients with adrenal insufficiency, median time to adrenal insufficiency diagnosis was 10.2months from neuroblastoma diagnosis, with cases more commonly occurring in patients with adrenal primary tumors (p = 0.0234). There were no other significant differences in demographic or clinical characteristics between high-risk patients with and without adrenal insufficiency. Adrenal insufficiency occurs more commonly in children with high-risk neuroblastoma than in non-high-risk cases, particularly those with adrenal primary tumors. These findings underscore the need for vigilant monitoring and screening for adrenal insufficiency during and after treatment. Future research should include larger, multi-institutional cohorts to better understand risk factors and optimize screening protocols.

Impact of Genomic Classifiers on Risk Stratification and Treatment Intensity in Patients With Localized Prostate Cancer : A Systematic Review.

Tissue-based genomic classifiers (GCs) have been developed to improve prostate cancer (PCa) risk assessment and treatment recommendations. To summarize the impact of the Decipher, Oncotype DX Genomic Prostate Score (GPS), and Prolaris GCs on risk stratification and patient-clinician decisions on treatment choice among patients with localized PCa considering first-line treatment. MEDLINE, EMBASE, and Web of Science published from January 2010 to August 2024. Two investigators independently identified studies on risk classification and treatment choice after GC testing for patients with localized PCa considering first-line treatment. Relevant data extracted by 1 researcher and overread by a second. Risk of bias (ROB) was assessed in duplicate. Ten studies reported risk reclassification after GC testing. In low ROB observational studies, very low- or low-risk patients with PCa were more likely to have their risk levels classified as the same or lower (GPS, 100% to 88.1%; Decipher, 87.2% to 82.9%; Prolaris, 76.9%). However, 1 randomized trial found that GC testing with GPS reclassified 34.5% of very low-risk and 29.4% of low-risk patients to a higher risk category. Twelve observational studies indicated that treatment decisions after GC testing either remained unchanged or slightly favored active surveillance. In contrast, analyses from a single randomized trial found fewer choices for active surveillance after GPS testing. Heterogeneity in screening patterns, risk-determination cutoffs, pathology, and clinical practices. Studies on treatment choice were moderate to high ROB. Although GC tests do not consistently influence risk classification or treatment decisions, the differences observed between observational and randomized studies highlight a need for well-designed trials to explore the role of GC tests in patients with newly diagnosed PCa considering first-line treatment. U.S. Department of Veterans Affairs. (PROSPERO: CRD42022347950).

Resistance to the herbicides haloxyfop and iodosulfuron is common in commercial ryegrass (Lolium) seed lines.

Ryegrass (Lolium spp.) is a key forage providing a $14 billion contribution to New Zealand's gross domestic product (GDP). However, ryegrass can also act as a weed and evolve resistance to herbicides used for its control. Farmers suspected that imported seed might contribute to resistance issues. Herbicide resistance frequencies were investigated in commercial ryegrass seed lines intended for multiplication in New Zealand. Samples from 56 basic seed lots and 52 unique cultivars sourced from regions including New Zealand, United States, Europe and Japan were planted in field trials. Seedlings were then sprayed with three common herbicides: glyphosate, iodosulfuron, and haloxyfop. Surviving plants were retested to confirm resistance. Resistance to haloxyfop and or iodosulfuron was detected in 79% of seed lines. However, frequencies were not significantly higher in imported lines (from United States and Europe) compared with New Zealand lines. Resistance was detected at frequencies between 0.00112% and 10% for haloxyfop and between 0.00212% and 14.28% for iodosulfuron Resistance to glyphosate was not found. There was no significant difference between the resistance detected in seed samples sourced from different seed companies. It was found that 63% of resistant lines had resistance frequencies rarer than 0.1%, but this is potentially problematic considering typical sowing rates. Imported versus domestic seed sources were not significantly different; they pose similar levels of resistance risk to farmers. Lolium multiflorum had a higher resistance frequency compared to Lolium perenne (although only six L. multiflorum lots were evaluated). Breeders should screen progeny of early crosses for herbicide resistance. © 2025 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Chilean Mediterranean forest on the verge of collapse? Evidence from a comprehensive risk analysis.

World forests are experiencing significant modification due to the confluence of climate change and deforestation, with Mediterranean forests facing particularly acute threats. The Chilean Sclerophyllous Mediterranean Forest is considered a world biodiversity hotspot, a restricted ecosystem type that is highly affected by global change drivers. Despite the high ecological and environmental importance of this ecosystem, an integrated assessment of its risk derived from climate and land-use change is lacking. This study estimates the level of risk of all sclerophyll forest stands in Chile, by assessing their exposure to several factors linked with climate change, land cover change, wildfires, change in the vegetation functional properties, and habitat fragmentation. We also generated a spatially explicit estimate of the main factors underlying the risk of each sclerophyllous forest stand. We constructed a multifactorial risk index based on the different analyzed variables, exploring the main drivers associated with the risk of each forest stand using principal components analysis with agglomerative hierarchical clustering. We found that 39.8% of sclerophyll forest stands reached a high or very high-risk index, with the highest levels concentrated between 32°S and 34°S. The vigor and net primary production of sclerophyll forest stands decreased in 90.9% and 86.6%, respectively. We identified three groups of forest stands: A) northern group (29.9°S to 33.5°S), which has experienced high decrease of net primary production and vegetation vigor; B) central group (32°S to 35°S), also affected by degradation and replacement by croplands; and C) southern group (34°S to 39°S), affected by drought and exotic forest plantations. The results of this study provided clarity on the current state of the sclerophyll forest, allowing for the identification of spatial differences in the risk and their underlying factors. Our results and data can be useful for informing policy and supporting sustainable management of government agencies and practitioners.

Research on the Prediction Model of Coal Spontaneous Combustion Hazard Level Based on IGWO-GRNN

ABSTRACT To accurately predict the risk level of spontaneous coal combustion, we introduce an improved grey wolf optimization strategy (IGWO) to optimize the generalized regression neural network (GRNN), thereby establishing the IGWO-GRNN coal spontaneous combustion risk level prediction model. The superiority of the IGWO algorithm over the grey wolf optimization algorithm (GWO), whale optimization algorithm (WOA) and particle swarm optimization algorithm (PSO) was verified. Fifty sets of sample data of spontaneous coal combustion in the mining area were selected as the research object, and the data were randomly divided into the training set and the test set according to the ratio of 8:2. The prediction results of the IGWO-GRNN prediction model were obtained and compared with those of the GWO-GRNN, GRNN, BP (Backpropagation), and GRU (Gated Recurrent Unit) models, and the absolute value of the relative error was introduced as an evaluation index of the model prediction accuracy. The results demonstrate that IGWO outperforms GWO, WOA, and PSO in terms of optimization efficiency, with the IGWO-GRNN prediction model yielding the most accurate results. Specifically, the maximum absolute value of the relative error does not exceed 4.27%, and the average relative error is only 3.29%, indicating a substantial improvement over the other models. Therefore, this study achieves high-precision prediction under small-sample data, which provides an important reference value for the small-sample prediction problem in the mining field.

Exploring the impact of built environment on traffic risk perception of school-aged children: A case study of old residential neighborhoods in Changsha City, Hunan Province, China.

The built environment of old residential neighborhoods poses heightened perceived traffic risks for school-aged children due to their limited cognitive ability to assess hazards, underdeveloped understanding of traffic patterns, and inadequate infrastructure in these areas. However, studies on the impacts of neighborhood environments on children's traffic risk perceptions remain limited. This study aims to reveal the influence of individual attributes, as well as macro- and micro-level environmental factors, on children's risk perception using a hierarchical ordered logit model with random effects. Data were collected through a questionnaire survey of 404 school-aged children across fifty old residential neighborhoods in Changsha, China. The results indicated that girls generally perceive higher levels of traffic risk than boys. At the macro-level, low population density and high activity facilities coverage were associated with reduced risk perceptions among children. At the micro-level, obstructed views of intersections, curbside parking, and road damage were found to increase risk perceptions among children. Additionally, random effects related to gender, intersection type, intersection visibility, curbside parking, and sidewalk availability suggested the influence of unobserved factors. The findings underscore the need for targeted interventions, such as improving intersection visibility, managing curbside parking, and repairing road damage, to mitigate traffic risks. Policymakers and urban designers should focus on these aspects to enhance safety and create child-friendly residential environments.

Holistic Assessment of Social, Environmental and Economic Impacts of Pipe Breaks: The Case Study of Vancouver

This paper presents a holistic assessment framework for the impacts of water distribution pipe breaks to promote environmentally sustainable and socially resilient cities. This framework considers social, environmental, and economic vulnerabilities as well as probabilities associated with pipe failure. The integration of these features provides a comprehensive approach to understanding infrastructure risks. Taking the city of Vancouver as a case study, the social vulnerability index (SVI) is obtained following the application of a cross-correlation matrix and principal component analysis (PCA) to identify the most influential among 33 selected variables from the 2021 census of the Canadian population. The Environmental Vulnerability Index (EVI) is evaluated by considering the park and floodplain areas. The Economic Vulnerability Index (ECI) is derived from the replacement cost of pipes. These indices offer valuable insights into the spatial distribution of vulnerabilities (consequences) across urban areas. Subsequently, the Consequence of Failure (COF) is computed by aggregating the three vulnerabilities with equal weights. Pipe probability of failure (POF) is evaluated by a Weibull model calibrated on real break data as a function of pipe age. This approach enables a dynamic evaluation of pipe deterioration over time. Risk is finally assessed by combining COF and POF for prioritizing pipe replacement and rehabilitation, with the final objective of mitigating the adverse impacts of infrastructure failure. The findings show the significant impact of ethnicity, socioeconomic indices, and education on the social vulnerability index. Moreover, the areas close to English Bay and Fraser River are more environmentally vulnerable. The pipes with high economic vulnerability are primarily concrete pipes, due to their expensive replacement costs. Finally, the risk framework resulting from the vulnerabilities and pipe break probabilities is used to rank the Vancouver City water distribution network pipes. This ranking system highlights critical areas requiring different levels of attention for infrastructure improvements. All the pipes and corresponding risks are illustrated in Vancouver maps, highlighting that the pipes associated with a very high level of risk are mostly in the south and north of Vancouver.

Influence of nearest neighbor distance and habitat structure on vigilance behavior

One of the important antipredator benefits of group living for prey species is collective vigilance that enhances early predator detection. Within the group, individuals monitor the behavior of others to gauge the level of risk in the environment. The nearest-neighbor distance is important as the information travels quickly and easily from the nearest individuals. I examined the vigilance behavior of free-ranging chital deer (Axis axis, Gir Protected Area, India) in response to the group size, nearest neighbor distance, and habitat structure (open versus dense vegetation). The vigilance behavior showed a weak negative response to increases in group size. Overall, the vigilance levels were significantly higher for animals that had distant neighbors. There was a significant interaction effect of habitat structure and the nearest neighbor distance on vigilance levels of chitals. However, this effect was only significantly different for individuals living in dense vegetation. Chitals respond more strongly to conspecific vigilance from their nearest companion in the denser mixed forest than open acacia grasslands. The results indicate that nearest neighbor distance and habitat structure interact in determining the vigilance behavior of group living ungulates and transmission of information within a social group.

Environmental risk assessment methodology for urban tropical lagoons based on feasible lines of evidence under limited resources conditions: Jacarepaguá Lagoon/Brazil.

Determining environmental risk levels posed to different urban lagoon can provide an important overview regarding the relative severity of the environmental degradation of these ecosystems, increasing the risks visibility, which can be used as an important decision-making tool to prioritize investments. Jacarepaguá Lagoon (JPAL) is part of a coastal lagoon system comprising four interconnected lagoons in Rio de Janeiro city, Southeastern Brazil. Real estate speculation and insufficient sanitation infrastructure resulted in untreated sewage discharge into this ecologically sensitive lagoon system. An Environmental Risk Assessment for Jacarepaguá lagoon was carried out integrating three Lines of Evidence (LoE): (i) Water Quality LoE; (ii) Ecotoxicological LoE; (iii) Ecological LoE to estimate an Environmental Risk Index (EnvRI) for this area. Surface water samples were collected during four bimonthly campaigns at five JPAL sampling points as well as an upstream reference area. The Water Quality LoE based on physicochemical parameters was used to estimate the Water Quality Risk Index (WQRI); the Ecotoxicological LoE based on two chronic ecotoxicity bioassays was used to estimate the Ecotoxicological Risk Index (EcotoxRI); and the Ecological LoE based on the richness and the abundance of phytoplankton taxa was used to estimate the Ecological Risk Index (EcoRI). The final EnvRI was then estimated by integrating these three Risk Indices. The WQRI (0.79 ± 0.07), as well as the EcotoxRI (0.80 ± 0.21), and the EcoRI (0.78 ± 0.13), were all in the range classified as very high. The EnvRI for JPAL was consequently also very high (0.81 ± 0.12), which indicates urgent intervention. EnvRI combined with high concentrations of organic compounds directly affected the diversity of phytoplankton species; however, it was observed that the high content of phytoplankton biomass also represents a part of the organic matter in question. The final goal was achieved: a feasible risk assessment tool available for comparison of different aquatic ecosystems, to facilitate decision making establishing priorities of investments under a limited resources scenario.

Sources identification and health risk assessment of heavy metals in total suspended particulates (TSP) in a geochemical anomaly area influenced by historical indigenous zinc smelting activities.

The superposition of heavy metals (HMs) from multiple anthropogenic sources in geochemical anomaly areas makes it difficult to discriminate prime sources in atmospheric HMs. This study utilized a combination of microscopic features, positive matrix factorisation, and Pb isotope fingerprints to trace the main sources of HMs bound to total suspended particulates (TSP) at a pollution site (Msoshui: MS) and control site (Lushan: LS) in northwestern Guizhou. The results reveal that the concentrations of Cd, Pb, Cr, As, Cu, Ni, and Zn in the TSP of LS are 3.97, 94.25, 2.93, 26.51, 3.15, 3.23, and 122.08ngm-3, respectively, in the 5years from 2018 to 2022, compared to 20.15, 960.28, 4.20, 41.50, 7.72, 2.95, and 1614.50ngm-3 in that of MS. In comparison with other cities and remote areas, the concentrations of TSP-bound Cd, Pb, As, and Zn at MS and LS are high. The microscopic morphology shows that atmospheric particles of LS are primarily derived from mineral dust, whereas those of MS are mainly affected by multiple anthropogenic sources. The results of the positive matrix factorisation model (PMF) suggest that the predominant sources of TSP-bound HMs at MS are industrial sources, mixed sources (coal combustion and traffic sources), and mineral dust, reflecting the noticeable superposition of industrial sources compared to those at LS. The Pb isotope analysis demonstrates that TSP-bound Pb principally derive from surface soil (61.33%) and vehicle exhaust & dust from burning coal (38.67%) at LS, while it is mainly influenced by surface soil (29.21%), smelter dust (27.50%), and vehicle exhaust & dust from burning coal (43.29%) at MS. Moreover, it also indicates that the lingering effects of historical indigenous zinc smelting activities continue to impact the atmospheric and surface soil conditions in northwestern Guizhou Province. Risk assessment indicates that although the non-carcinogenic risk for each element is within acceptable limits, the total non-carcinogenic risk of HMs exceeds the minimal risk level, and Cd and As are the primary contributors.

Source-oriented health risk assessment of soil potentially toxic elements based on Monte Carlo simulation in the upper reaches of Wei River Basin, China.

The natural environment and public health are gravely threatened by the enrichment of soil potentially toxic elements (PTEs). To explore the contamination level, sources and human health risks posed by PTEs, high-density soil sampling was carried out in the upper Wei River region (UWRR). The results demonstrated that the pollution risk and ecological risk in UWRR as a whole were at a low level, but there were moderate or higher ecological risks of Hg and Cd in some areas. Source analysis of soil PTEs was conducted via absolute principal component score multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) receptor models. APCS-MLR identified three potential sources, while the source division of PMF model was more detailed, which identified four potential sources: mining, coal combustion, machinery manufacturing and agricultural sources, with contribution percentages of 31%, 3%, 37% and 29% respectively. According to the probabilistic human health risk assessment (HHRA), the non-carcinogenic risk for adults was negligible, while that for children cannot be negligible. There were total carcinogenic risks for all populations, but the risk level was acceptable. The total cancer risk for children surpassed 1E-04 by 31.29%, implying a significant carcinogenic risk. Machinery manufacturing was found to be the most significant anthropogenic source of health concerns. This study offers an illustration of probabilistic risk assessment based on sources. The results of the study are favorable to provide new perspectives and scientific reference for soil PTE risk assessment and pollution control.

Trajectories of Justice Involved Youth: Changing Risk and Protective Factors for Violence

Forensic interventions aim to mitigate risk, yet research on change measured through repeated risk assessment is scarce, particularly regarding protective factors. This study examined changes in risk and protective factors during intervention and the impact of change on violent recidivism. Trajectories of 175 male justice involved youth with a history of violence were modeled using multilevel mixture modelling. Findings reveal that youths abstaining from violence displayed fewer risk factors and more protective factors at discharge. Assessments at discharge predicted recidivism. Change scores on several SAVRY/SAPROF-YV subscales over time demonstrated incremental predictive validity above and beyond assessments at discharge, emphasizing the necessity of personalized interventions and considering individual change alongside one’s overall risk level to inform more effective interventions. These insights advocate for balanced approaches informed by repeated assessments encompassing both risk and protective factors.

The role of visuals in the perceptions of risk and of self-efficacy and the behaviors towards the pandemic of Covid-19

The Covid-19 has spread rapidly, becoming a global health crisis. In crises, especially in public health problems such as a pandemic, it is important to reach the target audience effectively. In this process, the use of visuals helps to convey risk messages effectively. To control the pandemic and prevent its spread, individuals’ risk perception, self-efficacy and behaviors towards the pandemic are of great importance. The aim of this study is to measure how the visuals those individuals are exposed to about the Covid-19 pandemic affect their perceived risk level and self-efficacy, and how these relationships direct their behavior towards the pandemic. For the implementation of the study, data were collected from 410 people working in public institutions, in Türkiye. Structural equation modeling, t-test and Anova techniques analyzed the data collected in the survey conducted in the survey model. According to the research results, gender and educational status significantly affect employees’ attention to visuals and risk perception. According to the results of the research model, the research factors affect each other positively. Individuals’ interest in visuals increases their perceived risk and self-efficacy perceptions. Perceived risk and self efficacy for the epidemic, on the other hand, affect their behavior towards the epidemic.

Assessing heavy metal contamination in agricultural soils: a new GIS-based Probabilistic Pollution Index (PPI) – case study: Guarda Region, Portugal

ABSTRACT Soil contamination by heavy metals is a global agricultural problem, as these elements can be absorbed by plants and transferred to humans through the food pathway. Current contamination assessment methods rely on in situ sample collection, which restricts the evaluation process due to the number of samples that can be analysed and the associated costs. This study addresses the need for a more efficient and cost-effective approach to identifying areas at risk of heavy metal contamination without the logistical constraints of physical sampling. To meet this challenge, we developed a new Probabilistic Pollution Index (PPI), calculated by integrating GIS tools with an 8-parameter probability-risk matrix to identify agricultural areas potentially contaminated by heavy metals. The factors considered included roads, industrial sites, pH levels, soil organic matter content, terrain slope, soil texture, mining areas, and drainage. Each parameter was classified and reclassified to produce a contamination risk map, categorizing each pixel into five levels of risk. To test the PPI, data analysis, parameter classification, and reclassification were applied in the district of Guarda, Portugal. The PPI map revealed that the central portion of the Guarda municipality, along with specific zones in Celorico da Beira, Sabugal, Mêda, and Pinhel, exhibited a high-probability risk of contamination. Given the agricultural expanse within each municipality, enhanced monitoring of heavy metal levels was recommended for Mêda, Pinhel, and Vila Nova de Foz Côa. This index provides a scalable, cost-effective, and easily replicable tool for identifying potential contamination hotspots and the sources and processes of contamination. Designed as a first-line method for large-scale assessments, it supports governmental decision-making and facilitates targeted risk mitigation strategies through a low-cost approach.

Impact of Adverse Events on Neonatal Emergency Transport: Italian Experience.

To quantify and categorise retrospectively all adverse events occurring during unplanned neonatal emergency interhospital transfers conducted by the Transfer Service of the Spedali Civili di Brescia over 3 years. The revised data were extracted from specific questionnaires filled out by staff. The events were classified according to an adapted retrieval team model (PANSTAR); the risk level was assessed using an effective risk assessment score. In 340 transports, 74 adverse events were identified; 68% of them were perceived as due to human error. Most of the events (82%) occurred during the second stage of transportation. One of the 74 events was described as a potential cause of major injury to the patient; 61 of the 74 events were considered insignificant. No event was considered potentially catastrophic. Although most accidents do not pose a significant risk for the newborn, it is important to identify the few events that could potentially cause significant harm. Some phases of transportation are more at risk than others, and human error is confirmed as a predominant factor in most adverse events. Therefore, opportunities to reduce the number of events through education, training of neonatal retrieval teams and risk management should not be missed.

Climate Risk and Foreign Direct Investment Entry Mode

ABSTRACTThe paper examines how climate risk impacts the strategic entry mode choices—between greenfield investments and cross‐border mergers and acquisitions (M&As)—of multinational enterprises (MNEs) into foreign markets. Our study adds to existing literature through a cross‐countries empirical analysis and uses a newly developed dataset, the Multinational Revenue, Employment, and Investment Database (MREID), that accounts for how both physical and transition risks of climate change affect MNEs' entry mode choice. Physical risk refers to the tangible impacts of climate change such as extreme weather events, while transition risk involves regulatory and policy changes associated with moving towards a low‐carbon economy. Using data for 139 source countries and 134 destination countries over the period from 2010 to 2021, we find that an increase in the physical risk of climate change leads to MNEs choosing greenfield investment when entering a new market while a higher level of transition risk discourages greenfield investment. Physical risk has a negative and significant influence on MNEs' entry choice of using cross‐border M&A. There is a positive and significant correlation between transition risk and cross‐border M&A though such a relationship is not robust. Industrial‐level evidence shows a similar pattern in the majority of the industries. Our findings provide policymakers with guidelines helping to mitigate the negative impact of climate change on business decisions at the global level.

Associations of pro-inflammatory factors and IL-10 levels with degree of suicide risk in adolescents with depression

BackgroundDepression and suicidal behavior are associated with pro-inflammatory status in adults. However, differences in inflammatory levels among adolescents with depression at different suicide risk levels are unclear, and the connection between anti-inflammatory factors, which serve as vital for the immune system, and suicide needs to be explored.MethodsThis study recruited 111 adolescent patients with depression aged 13-18 and 23 healthy controls. Patients were divided into three subgroups according to suicidal ideation within the past week and history of suicide attempts. Severity of depression, suicidal ideation, and suicide risk were assessed using the Hamilton Depression Scale-17 (HAMD-17) and the Chinese version of the Beck Suicide Ideation Scale (BSI-CV). Plasma levels of IL-6, TNF-α, IFN-γ, IL-1β, and IL-10 in all participants were measured.ResultsPlasma levels of IL-6, TNF-α, IFN-γ, and IL-10 differed between the suicide risk subgroups, and the differences remained significant after controlling for severity of depressive symptoms using covariance analysis. Pairwise comparison indicated that plasma levels of these four cytokines in the high suicide risk group were higher than those in the low suicide risk group (all p<0.05), among which the level of IL-10 was significantly higher than that in the medium and low risk groups. IL-10 was positively correlated with the total score of the HAMD-17, BSI-CV, and suicidal ideation; the other four cytokines were also somewhat correlated with suicidal ideation (all p<0.05). IL-10 correlated positively with these four pro-inflammatory factors. Multiple linear regression analysis showed that IL-10 levels significant were associated with BSI-CV (β = 0.270, t = 2.897, p = 0.005) and HAMA-17 (β = 0.285, t = 3.041, p = 0.003) total scores. In binary logistic regression, after controlling for depressive symptoms, gender, age, BMI, and duration of illness: IL-10 level remained a risk factor for suicidal behavior (OR = 3.224, 95% CI 1.571-6.619 p = 0.001).ConclusionAdolescents with different suicide risk levels differed in plasma levels of pro-inflammatory factors and the anti-inflammatory factor IL-10. These differences were independent of depressive symptoms; high IL-10 levels may be a risk factor for suicidal behavior in depressed patients. Further research is needed to explore the relationship between anti-inflammatory factors and suicide.

Genetic medicine of familial and hereditary pancreatic cancer: Recent update in the era of precision cancer medicine.

In Japan, 5 years have passed since the initiation of precision cancer medicine, and recent data accumulation in familial pancreatic cancer (FPC) and hereditary pancreatic cancer is outstanding. Multigene germline panel tests (MGPTs) have revealed that 7%-18% of patients with pancreatic cancer (PC) harbor pathogenic germline variants (PGVs), almost equal to the levels of breast, ovarian, endometrial, and colorectal cancers, with a higher incidence in FPC (14%-26%). The majority of PGVs seen in PC patients are clinically actionable and associated with homologous recombination (HR) pathways (6%-10%, particularly BRCA1/2 in 5%-6%), and the clinical guidelines recommend or propose genetic testing for all PC patients. Consensus guidelines have been established for most of the hereditary syndromes associated with PC risks, and surveillances of the pancreas and other at-risk organs are recommended for PGV carriers. Hereditary breast and ovarian cancer (HBOC) is the commonest hereditary cancer syndrome that has moderately increasing life-time risks of PC (3%-7% in Western countries); however, recent Japanese research demonstrated a higher risk level (BRCA1: 16%, BRCA2: 14%). Moreover, recent evidence has suggested a risk linkage between PC and ovarian cancer in HBOC pedigrees. High scores of homologous recombination deficiency suggest biallelic dysfunction of BRCA or other HR-related genes, and the likely effectiveness of platinum agents and PARP inhibitors against PCs. Remote counseling and testing are possible option in the future genetic medicine. As PC ranks in the second commonest target of precision cancer medicine in Japan, we must treat the patients and manage their at-risk relatives efficiently.