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Because of the more emerging risks and stronger risk interactions, the risk of college campuses as well as students and staff received more and more attention. Current works on campus risk mostly focus on single-category factors, and few of them considered risk interactions. Therefore, an integrated model for assessing comprehensive risks on the campus is proposed to put forward risk reduction strategies. First, a comprehensive risk identification of the college campus is conducted by integrating the modified egg model and the fault tree. Then, DEMATEL (Decision-Making Trial and Evaluation Laboratory) is applied to quantify the complex risk interactions and determine the influential causes for further modelling. Finally, the Bayesian network is established for cause diagnosis, consequence prediction, and risk reduction. The identified most sensitive cause is alcohol use. In the case of the four sensitive causes simultaneously occurring, the probability of high campus risk will increase from 21.9% of the original to 39.4%. Moreover, an efficiency analysis of different risk reduction strategies is performed to determine the most efficient risk reduction strategy. The results indicate that the proposed methodology may of great significance for the risk reduction of the college campus in the changing age.

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The last 12 months have provided further evidence of the potential for cascading ecological and socio-political crises that were warned of 12 months ago. Then a consensus statement from the Regional Action on Climate Change Symposium warned: "the Earth's climatic, ecological, and human systems are converging towards a crisis that threatens to engulf global civilization within the lifetimes of children now living." Since then, the consequences of a broad set of extreme climate events (notably droughts, floods, and fires) have been compounded by interaction with impacts from multiple pandemics (including COVID-19 and cholera) and the Russia-Ukraine war. As a result, new connections are becoming visible between climate change and human health, large vulnerable populations are experiencing food crises, climate refugees are on the move, and the risks of water, food, and climate disruption have been visibly converging and compounding. Many vulnerable populations now face serious challenges to adapt. In light of these trends, this year, RACC identifies a range of measures to be taken at global and regional levels to bolster the resilience of these populations in the face of such emerging crises. In particular, at all scales, there is a need for globally available local data, reliable analytic techniques, community capacity to plan adaptation strategies, and the resources (scientific, technical, cultural, and economic) to implement them. To date, the rate of growth of the support for climate change resilience lags behind the rapid growth of cascading and converging risks. As an urgent message to COP27, it is proposed that the time is now right to devote much greater emphasis, global funding, and support to the increasing adaptation needs of vulnerable populations.

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BACKGROUND: Asparagine and aspartate homeostasis are linked with type 2 diabetes (T2D). This study aimed to explore whether asparagine and aspartate metabolism interacted with sex and age to increase the risk of T2D. METHODS: From 27 May 2015 to 3 August 2016, we consecutively retrieved 1032 T2D patients and 1522 subjects without T2D from a tertiary care hospital in Liaoning, China. Restricted cubic spline nested in the logistic regression was used to draw odds ratio curves of plasma asparagine to aspartate ratio for T2D by sex and age. Cut-off point was selected where curves went apart, indicating possible interaction. Addictive interactions of asparagine to aspartate ratio with sex or age and secondary interaction with copresence of unfavorable sex and age were further estimated using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S). RESULTS: Ratio of asparagine to aspartate > 1.5 was associated with elevated risk of T2D (OR 7.99, 95%CI 5.50 to 11.6), which was enhanced by female gender to 13.6, (95%CI 8.10-22.9) and by > 50 years of age to 28.7 (14.6-56.3), with significant additive interactions. There was a significant secondary-interaction of copresence of female sex and > 50 years of age with high asparagine to aspartate ratio for increased T2D risk with the OR being further increased to 34.4 (20.5-57.5). CONCLUSIONS: High asparagine to aspartate ratio was associated with markedly increased risk of T2D, which was further amplified by either female gender or > 50 years of age, and especially both.

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Due to their characteristics and multiple objectives, high-speed rail (HSR) projects carry more complex risks than conventional projects and high correlation and conductivity are among the associated risk factors. Previous risk assessment frameworks for rail infrastructure have ignored the effects of risk interactions that inflate risk levels, namely, risk coupling effects. Based on a system dynamics method, this paper develops a risk coupling model for HSR project risk assessments. A risk factor list is established from a literature review, and relationships analysed using a case study and expert interviews. System dynamics equations are constructed and their parameters obtained by expert evaluations of risk factors. The proposed model is applied to a real-world HSR project to demonstrate it in detail. The model can evaluate the risk levels of HSR projects during a simulation period. In particular, it can identify the key coupling effects that are the main increased risk. It provides a significant resource, using which HSR project managers can identify and mitigate risks.

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BACKGROUND: The COVID-19 pandemic has incurred significant disease burden worldwide, particularly on the elderly population. This study aims to explore how risks of coronavirus infection interact across age groups using data from South Korea. METHODS: Daily new COVID-19 cases from 10 March to 30 April 2020 were scraped from online open sources. A multivariate vector autoregressive model for time series of count data was used to examine the risk interactions across age groups. Case counts from previous days were included as predictors to dynamically examine the change of risk patterns. RESULTS: In South Korea, the risk of coronavirus infection among elderly people was significantly affected by other age groups. An increase in virus infection among people aged 20-39 was associated with a double risk of infection among elderly people. Meanwhile, an increase in virus infection among elderly people was also significantly associated with risks of infection among other age groups. The risks of infection among younger people were relatively unaffected by that of other age groups. CONCLUSIONS: Protecting elderly people from coronavirus infection could not only reduce the risk of infection among themselves but also ameliorate the risks of virus infection among other age groups. Such interventions should be effective and for the long term.

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A case-control study involving 750 cases with squamous-cell carcinoma of the head and neck (HNSCC) and an equal number of healthy controls was initiated to investigate the association of polymorphisms in the drug metabolizing genes cytochrome P450 1A1 (CYP1A1), CYP1B1, CYP2E1 and glutathione S-transferase M1 (GSTM1) with the risk of developing cancer. Attempts were also made to identify the role and nature of gene-gene and gene-environment interactions in modifying the susceptibility to HNSCC. Polymorphisms in drug metabolizing CYPs or GSTM1 showed modest associations with cancer risk. However, cases carrying haplotypes with variant alleles of both CYP1A1*2A and *2C or CYP1B1*2 and *3 or CYP2E1*5B and *6 were at significant risk of developing HNSCC. Likewise, cases carrying a combination of variant genotypes of CYPs and GSM1 (null) were at higher risk (up to 5-fold) of developing HNSCC. HNSCC risk also increased several-fold in cases carrying variant genotypes of CYPs who were regular tobacco smokers (8-18-fold), tobacco chewers (3-7-fold), or alcohol users (2-4-fold). Statistical analysis revealed a more than multiplicative interaction between combinations of the variant genotypes of CYPs and GSTM1 (null) and between variant genotypes and tobacco smoking or chewing or alcohol consumption, in both case-control and case-only designs. The data thus suggest that although polymorphisms in carcinogen-metabolizing CYPs may be a modest risk factor for developing HNSCC, gene-gene, and gene-environment interactions play a significant role in modifying the susceptibility to HNSCC.

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