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Abstract Background Lung cancer is one of the most lethal cancers worldwide and patient clinical outcomes seem influenced by their socioeconomic position (SEP). Since little has been investigated on this topic in the Italian context, our aim was to investigate the role of SEP in the care pathway of lung cancer patients in terms of diagnosis, treatment and mortality. Methods This observational retrospective cohort study included patients discharged in the Lazio Region with a lung cancer diagnosis between 2014 and 2017. In the main analysis, educational level was used as SEP measure. Multivariate models, adjusted for demographic and clinical variables, were applied to evaluate the association between SEP and study outcomes, stratified for metastatic (M) and non-metastatic (NM) cancer. We defined a diagnosis as 'delayed' when patients received their initial cancer diagnosis after an emergency department admission. Access to advanced lung cancer treatments (high-cost, novel and innovative treatments) and mortality were investigated within the 24-month period post-diagnosis. Moreover, two additional indicators of SEP were examined in the sensitivity analysis: one focusing on area deprivation and the other on income-based exemption. Results A total of 13,251 patients were identified (37.3% with metastasis). The majority were males (> 60%) and over half were older than 70 years. The distribution of SEP levels among patients was as follow: 31% low, 29% medium–low, 32% medium–high and 7% high. As SEP increased, the risks of receiving a delayed diagnosis ((high vs low: M: OR = 0.29 (0.23–0.38), NM: OR = 0.20 (0.16–0.25)) and of mortality ((high vs low M: OR = 0.77 (0.68–0.88) and NM: 0.61 (0.54–0.69)) decreased. Access to advanced lung cancer treatments increased in accordance with SEP only in the M cohort (high vs low: M: OR = 1.57 (1.18–2.09)). The primary findings were corroborated by sensitivity analysis. Conclusions Our study highlighted the need of public health preventive and educational programs in Italy, a country where the care pathway of lung cancer patients, especially in terms of diagnosis and mortality, appears to be negatively affected by SEP level.

Background: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. Objectives: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. Methods: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. Results: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0–7 (0.9 °C). An IQR increase in inter-day TV0–7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0–7 and inter-day TV0–7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. Conclusions: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.

Assessing the association between temperature frequency and mortality can provide insights into human adaptation to local ambient temperatures. We collected daily time-series data on mortality and temperature from 757 locations in 47 countries/regions during 1979–2020. We used a two-stage time series design to assess the association between temperature frequency and all-cause mortality. The results were pooled at the national, regional, and global levels. We observed a consistent decrease in the risk of mortality as the normalized frequency of temperature increases across the globe. The average increase in mortality risk comparing the 10th to 100th percentile of normalized frequency was 13.03% (95% CI: 12.17–13.91), with substantial regional differences (from 4.56% in Australia and New Zealand to 33.06% in South Europe). The highest increase in mortality was observed for high-income countries (13.58%, 95% CI: 12.56–14.61), followed by lower-middle-income countries (12.34%, 95% CI: 9.27–15.51). This study observed a declining risk of mortality associated with higher temperature frequency. Our findings suggest that populations can adapt to their local climate with frequent exposure, with the adapting ability varying geographically due to differences in climatic and socioeconomic characteristics.

Background: Evidence available on the associations between urban greenness and mental health is mainly based on cross-sectional studies and has relied on 2D indicators of greenness. This longitudinal study aimed at investigating the association between 2D and 3D indicators of green and grey spaces and incident mental health-related outcomes in a large population-based cohort. Methods: Our study used data from 593,894 Italian adults (≥30 years) from the Rome Longitudinal Study. Mental health outcomes were defined using either drug prescriptions (antidepressants, antipsychotics, lithium and other mood stabilisers, and anxiolytics, hypnotics and sedatives), or hospitalisation records (for schizophrenia spectrum disorder, depression, anxiety, stress-related and somatoform, or substance use disorders). We obtained 2D and 3D indicators of green and grey exposures including Normalized Difference Vegetation Index (NDVI), green volume, grey volume, number of trees, and Normalized Difference Green-Grey Volume Index around participants’ homes. Cox proportional hazards regression models were developed to estimate the association of green and grey space exposure and psychiatric conditions and medicine use, adjusted for relevant covariates. Results: We found beneficial associations of NDVI and the number of trees with antipsychotic and lithium and other mood stabiliser drugs. We also observed detrimental associations between grey volume and lithium and other mood stabilisers and anxiolytic, hypnotic and sedative drugs. Finally, we found a protective association of the NDGG with lithium and other mood stabilisers (HR: 0.977; 95% CI: 0.965–0.990) and anxiolytic, hypnotic and sedative drugs (HR: 0.851; 95% CI: 0.762–0.950). The associations for hospitalisation for psychiatric conditions were less consistent and generally not statistically significant. Conclusions: Findings suggested that higher greenness areas around residential addresses are associated with reduced use of drugs for psychiatric conditions, while the opposite is true for higher grey space exposure. The study highlights the importance of accurately characterising green and grey spaces, using novel exposure indicators.

Background: Recent epidemiological evidence suggests associations between air pollution exposure and major depressive disorders, but the literature is inconsistent for other mental illnesses. We investigated the associations of several air pollutants and road traffic noise with the incidence of different categories of mental disorders in a large population-based cohort. Methods: We enrolled 1,739,277 individuals 30 + years from the 2011 census in Rome, Italy, and followed them up until 2019. In detail, we analyzed 1,733,331 participants (mean age 56.43 +/- 15.85 years; 54.96 % female) with complete information on covariates of interest. We excluded subjects with prevalent mental disorders at baseline to evaluate the incidence (first hospitalization or co-pay exemption) of schizophrenia spectrum disorders, bipolar, anxiety, personality, or substance use disorders. In addition, we studied subjects with first prescriptions of antipsychotics, antidepressants, and mood stabilizers. Annual average concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO₂), Black Carbon (BC), ultrafine particles (UFP), and road traffic noise were assigned to baseline residential addresses. We applied Cox regression models adjusted for individual and area-level covariates. Results: Each interquartile range (1.13 µg/m3) increase in PM2.5 was associated with a hazard ratio (HR) of 1.070 (95 % confidence interval [CI]: 1.017, 1.127) for schizophrenia spectrum disorder, 1.135 (CI: 1.086, 1.186) for depression, 1.097 (CI: 1.030, 1.168) for anxiety disorders. Positive associations were also detected for BC and UFP, and with the three categories of drug prescriptions. Bipolar, personality, and substance use disorders did not show clear associations. The effects were highest in the age group 30–64 years, except for depression. Conclusions: Long-term exposure to ambient air pollution, especially fine and ultrafine particles, was associated with increased risks of schizophrenia spectrum disorder, depression, and anxiety disorders. The association of the pollutants with the prescriptions of specific drugs increases the credibility of the results.

Background: The epidemiological evidence on the interaction between heat and ambient air pollution on mortality is still inconsistent. Objectives: To investigate the interaction between heat and ambient air pollution on daily mortality in a large dataset of 620 cities from 36 countries. Methods: We used daily data on all-cause mortality, air temperature, particulate matter ≤ 10 μm (PM10), PM ≤ 2.5 μm (PM2.5), nitrogen dioxide (NO2), and ozone (O3) from 620 cities in 36 countries in the period 1995–2020. We restricted the analysis to the six consecutive warmest months in each city. City-specific data were analysed with over-dispersed Poisson regression models, followed by a multilevel random-effects meta-analysis. The joint association between air temperature and air pollutants was modelled with product terms between non-linear functions for air temperature and linear functions for air pollutants. Results: We analyzed 22,630,598 deaths. An increase in mean temperature from the 75th to the 99th percentile of city-specific distributions was associated with an average 8.9 % (95 % confidence interval: 7.1 %, 10.7 %) mortality increment, ranging between 5.3 % (3.8 %, 6.9 %) and 12.8 % (8.7 %, 17.0 %), when daily PM10 was equal to 10 or 90 μg/m3, respectively. Corresponding estimates when daily O3 concentrations were 40 or 160 μg/m3 were 2.9 % (1.1 %, 4.7 %) and 12.5 % (6.9 %, 18.5 %), respectively. Similarly, a 10 μg/m3 increment in PM10 was associated with a 0.54 % (0.10 %, 0.98 %) and 1.21 % (0.69 %, 1.72 %) increase in mortality when daily air temperature was set to the 1st and 99th city-specific percentiles, respectively. Corresponding mortality estimate for O3 across these temperature percentiles were 0.00 % (-0.44 %, 0.44 %) and 0.53 % (0.38 %, 0.68 %). Similar effect modification results, although slightly weaker, were found for PM2.5 and NO2. Conclusions: Suggestive evidence of effect modification between air temperature and air pollutants on mortality during the warm period was found in a global dataset of 620 cities.

Objectives Workers in the construction industry have been exposed to asbestos in various occupations. In Italy, a National Mesothelioma Registry has been implemented more than 20 years ago. Using cases selected from this registry and exploiting existing control data sets, we estimated relative risks for pleural mesothelioma (PM) among construction workers.Design Case–control study.Setting Cases from the National Mesothelioma Registry (2000–2018), controls from three previous case–control studies.Methods We selected male PM incident cases diagnosed in 2000–2018. Population controls were taken from three studies performed in six Italian regions within two periods (2002–2004 and 2012–2016). Age-adjusted and period-adjusted unconditional logistic regression models were fitted to estimate odds ratios (OR) for occupations in the construction industry. We followed two approaches, one (primary) excluding and the other (secondary) including subjects employed in other non-construction blue collar occupations for >5 years. For both approaches, we performed an overall analysis including all cases and, given the incomplete temporal and geographic overlap of cases and controls, three time or/and space restricted sensitivity analyses.Results The whole data set included 15 592 cases and 2210 controls. With the primary approach (4797 cases and 1085 controls), OR was 3.64 (2181 cases) for subjects ever employed in construction. We found elevated risks for blue-collar occupations (1993 cases, OR 4.52), including bricklayers (988 cases, OR 7.05), general construction workers (320 cases, OR 4.66), plumbers and pipe fitters (305 cases, OR 9.13), painters (104 cases, OR 2.17) and several others. Sensitivity analyses yielded very similar findings. Using the secondary approach, we observed similar patterns, but ORs were remarkably lower.Conclusions We found markedly increased PM risks for most occupations in the construction industry. These findings are relevant for compensation of subjects affected with mesothelioma in the construction industry.

IntroductionWhile there is consistent evidence on the effects of heat on workers' health and safety, the evidence on the resulting social and economic impacts is still limited. A scoping literature review was carried out to update the knowledge about social and economic impacts related to workplace heat exposure.MethodsThe literature search was conducted in two bibliographic databases (Web of Science and PubMed), to select publications from 2010 to April 2022.ResultsA total of 89 studies were included in the qualitative synthesis (32 field studies, 8 studies estimating healthcare-related costs, and 49 economic studies). Overall, consistent evidence of the socioeconomic impacts of heat exposure in the workplace emerges. Actual productivity losses at the global level are nearly 10% and are expected to increase up to 30–40% under the worst climate change scenario by the end of the century. Vulnerable regions are mainly low-latitude and low- and middle-income countries with a greater proportion of outdoor workers but include also areas from developed countries such as southern Europe. The most affected sectors are agriculture and construction. There is limited evidence regarding the role of cooling measures and changes in the work/rest schedule in mitigating heat-related productivity loss.ConclusionThe available evidence highlights the need for strengthening prevention efforts to enhance workers' awareness and resilience toward occupational heat exposure, particularly in low- and middle-income countries but also in some areas of developed countries where an increase in frequency and intensity of heat waves is expected under future climate change scenarios.

Objectives: We explored temporal variations in disease burden of ambient particulate matter 2.5 μm or less in diameter (PM2.5) and ozone in Italy using estimates from the Global Burden of Disease Study 2019.Methods: We compared temporal changes and percent variations (95% Uncertainty Intervals [95% UI]) in rates of disability adjusted life years (DALYs), years of life lost, years lived with disability and mortality from 1990 to 2019, and variations in pollutant-attributable burden with those in the overall burden of each PM2.5- and ozone-related disease.Results: In 2019, 467,000 DALYs (95% UI: 371,000, 570,000) were attributable to PM2.5 and 39,600 (95% UI: 18,300, 61,500) to ozone. The crude DALY rate attributable to PM2.5 decreased by 47.9% (95% UI: 10.3, 65.4) from 1990 to 2019. For ozone, it declined by 37.0% (95% UI: 28.9, 44.5) during 1990–2010, but it increased by 44.8% (95% UI: 35.5, 56.3) during 2010–2019. Age-standardized rates declined more than crude ones.Conclusion: In Italy, the burden of ambient PM2.5 (but not of ozone) significantly decreased, even in concurrence with population ageing. Results suggest a positive impact of air quality regulations, fostering further regulatory efforts.

Background: Urban areas are disproportionately affected by multiple pressures from overbuilding, traffic, air pollution, and heat waves that often interact and are interconnected in producing health effects. A new synthetic tool to summarize environmental and climatic vulnerability has been introduced for the city of Rome, Italy, to provide the basis for environmental and health policies. Methods: From a literature overview and based on the availability of data, several macro-dimensions were identified on 1,461 grid cells with a width of 1 km2 in Rome: land use, roads and traffic-related exposure, green space data, soil sealing, air pollution (PM2.5, PM10, NO2, C6H6, SO2), urban heat island intensity. The Geographically Weighted Principal Component Analysis (GWPCA) method was performed to produce a composite spatial indicator to describe and interpret each spatial feature by integrating all environmental dimensions. The method of natural breaks was used to define the risk classes. A bivariate map of environmental and social vulnerability was described. Results: The first three components explained most of the variation in the data structure with an average of 78.2% of the total percentage of variance (PTV) explained by the GWPCA, with air pollution and soil sealing contributing most in the first component; green space in the second component; road and traffic density and SO2 in the third component. 56% of the population lives in areas with high or very high levels of environmental and climatic vulnerability, showing a periphery-centre trend, inverse to the deprivation index. Conclusions: A new environmental and climatic vulnerability indicator for the city of Rome was able to identify the areas and population at risk in the city, and can be integrated with other vulnerability dimensions, such as social deprivation, providing the basis for risk stratification of the population and for the design of policies to address environmental, climatic and social injustice.

Abstract Coronavirus disease 2019 (COVID-19) is associated with an increased risk of thrombotic events. Ischemic stroke in COVID-19 patients entails high severity and mortality rates. Here we aimed to analyze cerebral thrombi of COVID-19 patients with large vessel occlusion (LVO) acute ischemic stroke to expose molecular evidence for SARS-CoV-2 in the thrombus and to unravel any peculiar immune-thrombotic features. We conducted a systematic pathological analysis of cerebral thrombi retrieved by endovascular thrombectomy in patients with LVO stroke infected with COVID-19 (n = 7 patients) and non-covid LVO controls (n = 23). In thrombi of COVID-19 patients, the SARS-CoV-2 docking receptor ACE2 was mainly expressed in monocytes/macrophages and showed higher expression levels compared to controls. Using polymerase chain reaction and sequencing, we detected SARS-CoV-2 Clade20A, in the thrombus of one COVID-19 patient. Comparing thrombus composition of COVID-19 and control patients, we noted no overt differences in terms of red blood cells, fibrin, neutrophil extracellular traps (NETs), von Willebrand Factor (vWF), platelets and complement complex C5b-9. However, thrombi of COVID-19 patients showed increased neutrophil density (MPO+ cells) and a three-fold higher Neutrophil-to-Lymphocyte Ratio (tNLR). In the ROC analysis both neutrophils and tNLR had a good discriminative ability to differentiate thrombi of COVID-19 patients from controls. In summary, cerebral thrombi of COVID-19 patients can harbor SARS-CoV2 and are characterized by an increased neutrophil number and tNLR and higher ACE2 expression. These findings suggest neutrophils as the possible culprit in COVID-19-related thrombosis. Graphical Abstract

Abstract Background Air pollution is one of the main concerns for the health of European citizens, and cities are currently striving to accomplish EU air pollution regulation. The 2020 COVID-19 lockdown measures can be seen as an unintended but effective experiment to assess the impact of traffic restriction policies on air pollution. Our objective was to estimate the impact of the lockdown measures on NO2 concentrations and health in the two largest Italian cities. Methods NO2 concentration datasets were built using data deriving from a 1-month citizen science monitoring campaign that took place in Milan and Rome just before the Italian lockdown period. Annual mean NO2 concentrations were estimated for a lockdown scenario (Scenario 1) and a scenario without lockdown (Scenario 2), by applying city-specific annual adjustment factors to the 1-month data. The latter were estimated deriving data from Air Quality Network stations and by applying a machine learning approach. NO2 spatial distribution was estimated at a neighbourhood scale by applying Land Use Random Forest models for the two scenarios. Finally, the impact of lockdown on health was estimated by subtracting attributable deaths for Scenario 1 and those for Scenario 2, both estimated by applying literature-based dose–response function on the counterfactual concentrations of 10 μg/m3. Results The Land Use Random Forest models were able to capture 41–42% of the total NO2 variability. Passing from Scenario 2 (annual NO2 without lockdown) to Scenario 1 (annual NO2 with lockdown), the population-weighted exposure to NO2 for Milan and Rome decreased by 15.1% and 15.3% on an annual basis. Considering the 10 μg/m3 counterfactual, prevented deaths were respectively 213 and 604. Conclusions Our results show that the lockdown had a beneficial impact on air quality and human health. However, compliance with the current EU legal limit is not enough to avoid a high number of NO2 attributable deaths. This contribution reaffirms the potentiality of the citizen science approach and calls for more ambitious traffic calming policies and a re-evaluation of the legal annual limit value for NO2 for the protection of human health.

Abstract Background Venous thromboembolisms (VTE) are one of the most frequent cause among the cardiovascular diseases. Despite the association between long-term exposure to air pollution and cardiovascular outcomes have been widely explored in epidemiological literature, little is known about the air pollution related effects on VTE. We aimed to evaluate this association in a large administrative cohort in 15 years of follow-up. Methods Air pollution exposure (NO2, PM10 and PM2.5) was derived by land use regression models obtained by the ESCAPE framework. Administrative health databases were used to identify VTE cases. To estimate the association between air pollutant exposures and risk of hospitalizations for VTE (in total and divided in deep vein thrombosis (DVT) and pulmonary embolism (PE)), we used Cox regression models, considering individual, environmental (noise and green areas), and contextual characteristics. Finally, we considered potential effect modification for individual covariates and previous comorbidities. Results We identified 1,954 prevalent cases at baseline and 20,304 cases during the follow-up period. We found positive associations between PM2.5 exposures and DVT, PE and VTE with hazard ratios (HRs) up to 1.082 (95% confidence intervals: 0.992, 1.181), 1.136 (0.994, 1.298) and 1.074 (0.996, 1.158) respectively for 10 μg/m3 increases. The association was stronger in younger subjects ( 70 years old) and among those who had cancer. Conclusion The effect of pollutants on PE and VTE hospitalizations, although marginally non-significant, should be interpreted as suggestive of a health effect that deserves attention in future studies.

Abstract Objective To conduct a systematic review to evaluate the association between residential or occupational short- and long–term exposure to odour pollution from industrial sources and the health status of the exposed population. Methods The searches were conducted in Medline, EMBASE and Scopus in April 2021. Exposure to an environmental odour from industrial sources in population resident near the source or in workers was considered. We considered outcomes for which there was a biological plausibility, such as wheezing and asthma, cough, headache, nausea and vomiting (primary outcomes). We also included stress-related symptoms and novel outcomes (e.g. mood states). Risk of bias was evaluated using the OHAT tool. For primary outcomes, when at least 3 studies provided effect estimates by comparing exposed subjects versus not exposed, we pooled the study-specific estimates of odour-related effect using random effects models. Heterogeneity was evaluated with Higgins I2. Results Thirty studies were eligible for this review, mainly cross-sectional (n = 23). Only one study involved school-age children and two studies involved workers. Only five studies reported odour effects on objective laboratory or clinical outcomes. Animal Feeding Operations and waste were the most common industrial sources. The overall odds ratios in exposed versus not exposed population were 1.15 (95% CI 1.01 to 1.29) for headache (7 studies), 1.09 (95% CI 0.88 to 1.30) for nausea/vomiting (7 studies), and 1.27 (95% CI 1.10 to 1.44) for cough/phlegm (5 studies). Heterogeneity was a moderate concern. Overall, the body of evidence was affected by a definitely high risk of bias in exposure and outcome assessment since most studies used self-reported information. Conclusions Findings underline the public health importance of odour pollution for population living nearby industrial odour sources. The limited evidence for most outcomes supports the need for high quality epidemiological studies on the association between odour pollution and its effects on human health.

Archival documents and artworks stored in libraries frequently undergo degradative processes promoted by the so-called “biodeteriogens” that inhabit these places. A renewed interest in plant-derived products has arisen in those research groups focusing on cultural heritage preservation and looking for new and safe disinfection techniques. In this view, essential oils (EOs) and their volatile organic constituents are very appealing thanks to their versatility of action. A literature survey of the scientific publications involving EOs and/or their major constituents related to the conservation of paper items of cultural heritage interest is presented here, aiming to reveal benefits and limitations of such peculiar plant-derived compounds.

Summary: Background: Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000–19. Methods: In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000–19. Temperature variability was calculated as the SD of the average of the same and previous days’ minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades. Findings: An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901–2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2–4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7–5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3–10·4), followed by Europe (4·4%, 2·2–5·6) and Africa (3·3, 1·9–4·6). Interpretation: Globally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability. Funding: Australian Research Council, Australian National Health & Medical Research Council.

Summary: Here, we present a comprehensive protocol for the generation and functional characterization of chimeric antigen receptor (CAR) T cells and their products by mass cytometry in a reproducible and scalable manner. We describe the production of CAR T cells from human peripheral blood mononuclear cells. We then detail a three-step staining protocol with metal-labeled antibodies and the subsequent mass cytometry analysis. This protocol allows simultaneous characterization of CAR T cell intracellular signaling, activation, proliferation, cytokine production, and phenotype in a single assay.

Abstract Background Standardized mortality surveillance data, capable of detecting variations in total mortality at population level and not only among the infected, provide an unbiased insight into the impact of epidemics, like COVID-19 (Coronavirus disease). We analysed the temporal trend in total excess mortality and deaths among positive cases of SARS-CoV-2 by geographical area (north and centre-south), age and sex, taking into account the deficit in mortality in previous months. Methods Data from the Italian rapid mortality surveillance system was used to quantify excess deaths during the epidemic, to estimate the mortality deficit during the previous months and to compare total excess mortality with deaths among positive cases of SARS-CoV-2. Data were stratified by geographical area (north vs centre and south), age and sex. Results COVID-19 had a greater impact in northern Italian cities among subjects aged 75–84 and 85+ years. COVID-19 deaths accounted for half of total excess mortality in both areas, with differences by age: almost all excess deaths were from COVID-19 among adults, while among the elderly only one third of the excess was coded as COVID-19. When taking into account the mortality deficit in the pre-pandemic period, different trends were observed by area: all excess mortality during COVID-19 was explained by deficit mortality in the centre and south, while only a 16% overlap was estimated in northern cities, with quotas decreasing by age, from 67% in the 15–64 years old to 1% only among subjects 85+ years old. Conclusions An underestimation of COVID-19 deaths is particularly evident among the elderly. When quantifying the burden in mortality related to COVID-19, it is important to consider seasonal dynamics in mortality. Surveillance data provides an impartial indicator for monitoring the following phases of the epidemic, and may help in the evaluation of mitigation measures adopted.

Abstract Background Hexachlorocyclohexane is a synthetic chemical with several isomers, including β-Hexachlorocyclohexane (β-HCH). In 2005, a large contamination of crude milk from some bovine farms along the Sacco River (Central Italy) was detected; it was related to the illegal disposal of large quantities of processing waste by a chemical industry of the area. A biomonitoring study, conducted in 2007 on a sample of the residing population, found high values of β-HCH in people living close to the river. These results led to the establishment of a clinical and epidemiological surveillance program on all the exposed population. The aim of the study was to evaluate the determinants of β-HCH blood levels in people living within 1 Km of the Sacco River, focusing on the role of specific foods, body mass index and risk factors not yet identified. Methods The program involved all people living within 1 km of the river. A descriptive analysis of β-HCH blood levels was done in relation to the potential determinants including specific foods. Regression analysis was used to study the association between potential determinants and (natural log) β-HCH haematic concentration. The results were expressed as geometric mean ratios (GMR). To take into account similarities within the families we adjusted for family clustering. Results A total of 602 subjects (87.2%) agreed to participate in the surveillance. The β-HCH geometric mean serum concentration was 72 ng/g lipid. The regression analysis showed that being female (GMR: 1.32, 95%CI: 1.14–1.53), elderly (GMR> 70yy: 10.04, 95%CI: 6.65–15.15), obese (GMR: 1.63, 95%CI: 1.28–2.08), eating food of local/own production (GMR 1.47, 95%CI: 1.15–1.88) and using water from private wells (GMRdrink:1.47, 95%CI: 1.00–2.14 and GMRwash: 1.48, 95%CI: 1.17–1.87) were associated with higher β-HCH values. There was inverse association with breastfeeding (GMR: 0.64, 95%CI: 0.47–0.86). The focus on specific foods showed that the most important factors were eggs and beef. Conclusions The study indicated a greater contamination for older people, and those drinking and washing with water from private wells and consuming locally produced food, especially eggs and beef.

ObjectivesUnintentional injuries such as falls, are particularly frequent in early childhood. To date, epidemiological studies in this field have been carried out using routine data sources or registries and many studies were observational studies with a cross-sectional design. The aims of the study are to describe unintentional injuries in the first two years of life in the Piccolipiù birth cohort, and to investigate the association between mother and children characteristics and the First Event of Raised surface Fall (FERF).MethodsThis longitudinal observational study included 3038 children from an Italian birth cohort. Data on socio-demographic factors, socio-economic indicators, maternal health and lifestyle characteristics and child's sleeping behavior, obtained from questionnaires completed at birth, 12 and 24 months of age, were considered in the analyses as potential risk factors of FERF. Time of occurrence of FERF was analyzed using the Kaplan-Meier method. The multivariable analysis for time to event was carried out using a Cox proportional hazards model.ResultsFalls from raised surfaces are the leading cause of unintentional injuries in the cohort with 610 (21.1%) and 577 (20.0%) cases among children during the first and second year of life, respectively. An increased risk of FERF was associated with several risk factors: maternal psychological distress (HR 1.41, 95%CI 1.10-1.81), maternal alcohol intake (HR 1.26, 95%CI 1.10-1.45), and child's sleeping problems (HR 1.28, 95%CI 1.09-1.51). Children with older aged mothers (HR 0.98, 95%CI 0.96-0.99) and living in northern Italy (HR 0.64, 95%CI 0.55-0.75) had a lower risk of FERF.ConclusionThe results of the study suggest that a higher risk of FERF is associated with socio-demographic factors, maternal characteristics and child sleeping behavior that could hinder parent empowerment.

Postharvest fruit loss is caused by the absence of advanced handling and storage technologies and the quiescent presence of fungal pathogens. Therefore, there is a growing demand for sustainable decisions for the planet. This study focused on the use of two types of edible coatings: one was based on the essential oil of Origanum vulgare L. subsp. viridulum with Aloe arborescens Mill. gel (EC1), and the other was based on the hydrolate only (EC2). These treatments were applied to provide defense against fungal infections in papaya (Carica papaya L. cv Solo), and the storage time was 25 days (T5 ± 1 °C). Fruits coated with EC1 were more contaminated with fungal pathogens than both control (CTR) and EC2 fruit. EC2 showed a statistically lower decay index than CTR and EC1 and maintained its organoleptic characteristics better, showing a 15% loss of firmness after 25 days of storage. Furthermore, the lowest decay index (1.14 after 25 days) was found for the EC1 and CTR. These findings suggest that the use of hydrolate can be useful for extending the shelf life and maintaining the quality of papaya fruit, representing an alternative to the use of synthetic fungicides for food safety.

Summary: Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. Funding: Australian Research Council and the Australian National Health and Medical Research Council.

Abstract Background Few studies have explored the role of air pollution in neurodegenerative processes, especially various types of dementia. Our aim was to evaluate the association between long-term exposure to air pollution and first hospitalization for dementia subtypes in a large administrative cohort. Methods We selected 350,844 subjects (free of dementia) aged 65–100 years at inclusion (21/10/2001) and followed them until 31/12/2013. We selected all subjects hospitalized for the first time with primary or secondary diagnoses of various forms of dementia. We estimated the exposure at residence using land use regression models for nitrogen oxides (NOx, NO2) and particulate matter (PM) and a chemical transport model for ozone (O3). We used Cox models to estimate the association between exposure and first hospitalization for dementia and its subtypes: vascular dementia (Vd), Alzheimer’s disease (Ad) and senile dementia (Sd). Results We selected 21,548 first hospitalizations for dementia (7497 for Vd, 7669 for Ad and 7833 for Sd). Overall, we observed a negative association between exposure to NO2 (10 μg/m3) and dementia hospitalizations (HR = 0.97; 95% CI: 0.96–0.99) and a positive association between exposure to O3, NOx and dementia hospitalizations, (O3: HR = 1.06; 95% CI: 1.04–1.09 per 10 μg/m3; NOx: HR = 1.01; 95% CI: 1.00–1.02 per 20 μg/m3).H. Exposure to NOx, NO2, PM2.5, and PM10 was positively associated with Vd and negatively associated with Ad. Hospitalization for Sd was positively associated with exposure to O3 (HR = 1.20; 95% CI: 1.15–1.24 per 10 μg/m3). Conclusions Our results showed a positive association between exposure to NOx and O3 and hospitalization for dementia and a negative association between NO2 exposure and hospitalization for dementia. In the analysis by subtype, exposure to each pollutants (except O3) demonstrated a positive association with vascular dementia, while O3 exposure was associated with senile dementia. The results regarding vascular dementia are a clear indication that the brain effects of air pollution are linked with vascular damage.

Abstract Background In Europe, it is estimated that one third of women had experienced at least one physical or sexual violence after their 15. Taking into account the severe health consequences, the Emergency Department (ED), may offer an opportunity to recognize when an aggression is part of the spectrum of violence. This study applies Social Network analysis (SNA) to ED data in the Lazio region with the objective to identify patterns of diagnoses, within all the ED accesses of women experiencing an aggression, that are signals for gender-based violence against women. We aim to develop a risk assessment tool for ED professionals in order to strength their ability to manage victims of violence. Methods A cohort of 124,691 women aged 15–70 with an ED visit for aggression between 2003 and 2015 was selected and, for each woman, the ED history of diagnoses and traumas was reconstructed. SNA was applied on all these diagnoses and traumas, including also 9 specific violence diagnoses. SNA community detection algorithms and network centrality measures were used to detect diagnostic patterns more strongly associated to violence. A logistic model was developed to validate the capability of these patterns to predict the odds for a woman of having an history of violence. Model results were summed up into a risk chart. Results Among women experiencing an aggression, SNA identified four communities representing specific violence-related patterns of diagnoses. Diagnoses having a central role in the violence network were alcohol or substance abuse, pregnancy-related conditions and psychoses. These high-risk violence related patterns accounted for at most 20% of our cohort. The logistic model had good predictive accuracy and predictive power confirming that diagnosis patterns identified through the SNA are meaningful in the violence recognition. Conclusions Routine ED data, analyzed using SNA, can be a first-line warning to recognize when an aggression related access is part of the spectrum of gender-based violence against women. Increasing the available number of predictors, such procedures may be proven to support ED staff in identifying early signs of violence to adequately support the victims and mitigate the harms.

Particulate matter (PM) air pollution is one of the major causes of death worldwide, with demonstrated adverse effects from both short-term and long-term exposure. Most of the epidemiological studies have been conducted in cities because of the lack of reliable spatiotemporal estimates of particles exposure in nonurban settings. The objective of this study is to estimate daily PM10 (PM

Two wild populations of Helichrysum (Mill.) located at Elba Island (Tuscan Archipelago, Central Italy) were morphologically and phytochemically analyzed to taxonomically identify H. litoreum (population A) and H. italicum subsp. italicum (population B). Micromorphological and histochemical analyses were performed on the indumentum using Scanning Electron Microscope (SEM) and Light Microscope (LM). Morphometric analyses on vegetative and reproductive traits were also conducted. Finally, a chemotaxonomic analysis was carried out on the terpene profile of flowers, leaves and bark tissues using gas chromatography (GC-MS). Results suggested that morphological discriminant traits were mainly in leaves and cypselae glandular tissues. Phytochemical analysis indicated that a high relative content of α-pinene and β-caryophyllene were the main markers for population A, while a high relative content of neryl-acetate, α-curcumene, isoitalicene and italicene, especially in the terpene profile of bark tissue, were the main compounds for discriminating population B. The analysis suggested that the wild population A could be mainly ascribed to H. litoreum, whilst population B is defined by H. italicum.