Psychological Resilience after Hurricane Sandy: the Influence of Individual- and Community-level Factors on Mental Health after a Llarge-scale Natural Disaster.

Several individual-level factors are known to promote psychological resilience in the aftermath of disasters. Far less is known about the role of community-level factors in shaping postdisaster mental health. The purpose of this study was to explore the influence of both individual- and community-level factors on resilience after Hurricane Sandy. A representative sample of household residents (N = 418) from 293 New York City census tracts that were most heavily affected by the storm completed telephone interviews approximately 13–16 months postdisaster. Multilevel multivariable models explored the independent and interactive contributions of individual- and community-level factors to posttraumatic stress and depression symptoms. At the individual-level, having experienced or witnessed any lifetime traumatic event was significantly associated with higher depression and posttraumatic stress, whereas demographic characteristics (e.g., older age, non-Hispanic Black race) and more disaster-related stressors were significantly associated with higher posttraumatic stress only. At the community-level, living in an area with higher social capital was significantly associated with higher posttraumatic stress. Additionally, higher community economic development was associated with lower risk of depression only among participants who did not experience any disaster-related stressors. These results provide evidence that individual- and community-level resources and exposure operate in tandem to shape postdisaster resilience

The geography of post-disaster mental health: spatial patterning of psychological vulnerability and resilience factors in New York City after Hurricane Sandy

Background: Only very few studies have investigated the geographic distribution of psychological resilience and associated mental health outcomes after natural or man made disasters. Such information is crucial for location-based interventions that aim to promote recovery in the aftermath of disasters. The purpose of this study therefore was to investigate geographic variability of (1) posttraumatic stress (PTS) and depression in a Hurricane Sandy affected population in NYC and (2) psychological vulnerability and resilience factors among affected areas in NYC boroughs. Methods: Cross-sectional telephone survey data were collected 13 to 16 months post-disaster from household residents (N = 418 adults) in NYC communities that were most heavily affected by the hurricane. The Posttraumatic Stress Checklist for DSM-5 (PCL-5) was applied for measuring posttraumatic stress and the nine-item Patient Health Questionnaire (PHQ-9) was used for measuring depression. We applied spatial autocorrelation and spatial regimes regression analyses, to test for spatial clusters of mental health outcomes and to explore whether associations between vulnerability and resilience factors and mental health differed among New York City\u27s five boroughs . Results: Mental health problems clustered predominantly in neighborhoods that are geographically more exposed towards the ocean indicating a spatial variation of risk within and across the boroughs. We further found significant variation in associations between vulnerability and resilience factors and mental health. Race/ethnicity (being Asian or non-Hispanic black) and disaster-related stressors were vulnerability factors for mental health symptoms in Queens, and being employed and married were resilience factors for these symptoms in Manhattan and Staten Island. In addition, parental status was a vulnerability factor in Brooklyn and a resilience factor in the Bronx. Conclusions: We conclude that explanatory characteristics may manifest as psychological vulnerability and resilience factors differently across different regional contexts. Our spatial epidemiological approach is transferable to other regions around the globe and, in the light of a changing climate, could be used to strengthen the psychosocial resources of demographic groups at greatest risk of adverse outcomes pre-disaster. In the aftermath of a disaster, the approach can be used to identify survivors at greatest risk and to plan for targeted interventions to reach them

AKT regulates NPM dependent ARF localization and p53mut stability in tumors

Nucleophosmin (NPM) is known to regulate ARF subcellular localization and MDM2 activity in response to oncogenic stress, though the precise mechanism has remained elusive. Here we describe how NPM and ARF associate in the nucleoplasm to form a MDM2 inhibitory complex. We find that oligomerization of NPM drives nucleolar accumulation of ARF. Moreover, the formation of NPM and ARF oligomers antagonizes MDM2 association with the inhibitory complex, leading to activation of MDM2 E3-ligase activity and targeting of p53. We find that AKT phosphorylation of NPM-Ser48 prevents oligomerization that results in nucleoplasmic localization of ARF, constitutive MDM2 inhibition and stabilization of p53. We also show that ARF promotes p53 mutant stability in tumors and suppresses p73 mediated p21 expression and senescence. We demonstrate that AKT and PI3K inhibitors may be effective in treatment of therapeutically resistant tumors with elevated AKT and carrying gain of function mutations in p53. Our results show that the clinical candidate AKT inhibitor MK-2206 promotes ARF nucleolar localization, reduced p53(mut) stability and increased sensitivity to ionizing radiation in a xenograft model of pancreatic cancer. Analysis of human tumors indicates that phospho-S48-NPM may be a useful biomarker for monitoring AKT activity and in vivo efficacy of AKT inhibitor treatment. Critically, we propose that combination therapy involving PI3K-AKT inhibitors would benefit from a patient stratification rationale based on ARF and p53(mut) status

A climate-conditioned catastrophe risk model for UK flooding

We present a transparent and validated climate-conditioned catastrophe flood model for the UK, that simulates pluvial, fluvial and coastal flood risks at 1 arcsec spatial resolution (∼ 20–25 m). Hazard layers for 10 different return periods are produced over the whole UK for historic, 2020, 2030, 2050 and 2070 conditions using the UK Climate Projections 2018 (UKCP18) climate simulations. From these, monetary losses are computed for five specific global warming levels above pre-industrial values (0.6, 1.1, 1.8, 2.5 and 3.3 ∘C). The analysis contains a greater level of detail and nuance compared to previous work, and represents our current best understanding of the UK's changing flood risk landscape. Validation against historical national return period flood maps yielded critical success index values of 0.65 and 0.76 for England and Wales, respectively, and maximum water levels for the Carlisle 2005 flood were replicated to a root mean square error (RMSE) of 0.41 m without calibration. This level of skill is similar to local modelling with site-specific data. Expected annual damage in 2020 was GBP 730 million, which compares favourably to the observed value of GBP 714 million reported by the Association of British Insurers. Previous UK flood loss estimates based on government data are ∼ 3× higher, and lie well outside our modelled loss distribution, which is plausibly centred on the observations. We estimate that UK 1 % annual probability flood losses were ∼ 6 % greater for the average climate conditions of 2020 (∼ 1.1 ∘C of warming) compared to those of 1990 (∼ 0.6 ∘C of warming), and this increase can be kept to around ∼ 8 % if all countries' COP26 2030 carbon emission reduction pledges and “net zero” commitments are implemented in full. Implementing only the COP26 pledges increases UK 1 % annual probability flood losses by 23 % above average 1990 values, and potentially 37 % in a “worst case” scenario where carbon reduction targets are missed and climate sensitivity is high.</p

Estimates of present and future flood risk in the conterminous United States

Past attempts to estimate rainfall-driven flood risk across the US either have incomplete coverage, coarse resolution or use overly simplified models of the flooding process. In this paper, we use a new 30m resolution model of the entire conterminous US with a 2D representation of flood physics to produce estimates of flood hazard, which match to within 90% accuracy the skill of local models built with detailed data. These flood depths are combined with exposure datasets of commensurate resolution to calculate current and future flood risk. Our data show that the total US population exposed to serious flooding is 2.6–3.1 times higher than previous estimates, and that nearly 41 million Americans live within the 1% annual exceedance probability floodplain (compared to only 13 million when calculated using FEMA flood maps). We find that population and GDP growth alone are expected to lead to significant future increases in exposure, and this change may be exacerbated in the future by climate change

A five-antigen Esx-5a fusion delivered as a prime-boost regimen protects against M.tb challenge

The development of tuberculosis (TB) vaccines has been hindered by the complex nature of Mycobacterium tuberculosis (M.tb) and the absence of clearly defined immune markers of protection. While Bacillus Calmette-Guerin (BCG) is currently the only licensed TB vaccine, its effectiveness diminishes in adulthood. In our previous research, we identified that boosting BCG with an intranasally administered chimpanzee adenovirus expressing the PPE15 antigen of M.tb (ChAdOx1.PPE15) improved its protection. To enhance the vaccine’s efficacy, we combined PPE15 with the other three members of the Esx-5a secretion system and Ag85A into a multi-antigen construct (5Ag). Leveraging the mucosal administration safety of ChAdOx1, we targeted the site of M.tb infection to induce localized mucosal responses, while employing modified vaccinia virus (MVA) to boost systemic immune responses. The combination of these antigens resulted in enhanced BCG protection in both the lungs and spleens of vaccinated mice. These findings provide support for advancing ChAdOx1.5Ag and MVA.5Ag to the next stages of vaccine development