Substantial impact of mobility restrictions on reducing COVID-19 incidence in Italy in 2020

Italy was the first country after China to be severely affected by the COVID-19 pandemic, in early 2020. The country responded swiftly to the outbreak with a nationwide two-step lockdown, the first one light, and the second one tight. By analysing 2020 national mobile phone movements, we assessed how lockdown compliance influenced its efficacy

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Systematic Review and Meta-analysis on Association Between Air Pollutants and Hippocampal Volume from Magnetic Resonance Imaging in Adults

BACKGROUND AND AIM: The neurotoxicity of air pollutants has been actively investigated in recent years, and there is increasing epidemiological evidence suggesting that air pollution can adversely affect the central nervous system. In neurodegenerative disease, one important diagnostic biomarker is volume reduction in a key brain structure, the hippocampus, as assessed with neuroimaging techniques. Few epidemiological articles investigated the association of hippocampal volume with air pollution, with inconsistent results. In this paper, we aimed to estimate such association through a systematic review and meta-analysis. METHODS: Scopus and PubMed literature databases were searched through 31 March 2021. Eligibility criteria were: 1) assessment of air pollutant levels; 2) assessment of hippocampal volume through structural magnetic resonance imaging; 3) reporting of correlation coefficients along with standard error. We performed a meta-analysis using a random-effects model. RESULTS:We retrieved four studies using linear regression models to evaluate the possible effect of air pollutants on hippocampal volume of adult populations. The investigated air pollutants were nitrogen dioxide (NO2) and particulate matter, with diameter 642.5\ub5m (PM2.5) and 6410\u3bcm (PM10). All studies used a similar methodology based on standard spatial coordinates of images, and considered intracranial volume as a covariate. We found that hippocampal volume was inversely associated with PM2.5 concentration (\u3b2 regression coefficient -7.90, 95% confidence interval (CI) -14.60 to -1.20) and more slightly with PM10 concentrations (\u3b2 -1.70, 95%CI -3.96 to 0.57), whereas no association with NO2 concentrations emerged (\u3b2 -0.29, 95%CI -1.13 to 0.55). CONCLUSIONS:Our results suggest that PM2.5 and less clearly PM10 have an adverse effect on hippocampal volume, a phenomenon associated with cognitive decline and increased risk of neurodegenerative disease. These epidemiologic findings appear to be biologically plausible especially for PM2.5, also taking into account some studies carried out in animals. KEYWORDS: Neurotoxicity, Neuroimaging, Magnetic Resonance Imaging, Hippocampus, Meta-analysis, Nitrogen dioxid

The association between air pollutants and hippocampal volume from magnetic resonance imaging: A systematic review and meta-analysis

Growing epidemiological evidence suggests that air pollution may increase the risk of cognitive decline and neurodegenerative disease. A hallmark of neurodegeneration and an important diagnostic biomarker is volume reduction of a key brain structure, the hippocampus. We aimed to investigate the possibility that outdoor air nitrogen dioxide (NO2) and particulate matter with diameter ≤2.5 μm (PM2.5) and ≤10 μm (PM10) adversely affect hippocampal volume, through a meta-analysis. We considered studies that assessed the relation between outdoor air pollution and hippocampal volume by structural magnetic resonance imaging in adults and children, searching in Pubmed and Scopus databases from inception through July 13, 2021. For inclusion, studies had to report the correlation coefficient along with its standard error or 95% confidence interval (CI) between air pollutant exposure and hippocampal volume, to use standard space for neuroimages, and to consider at least age, sex and intracranial volume as covariates or effect modifiers. We meta-analyzed the data with a random-effects model, considering separately adult and child populations. We retrieved four eligible studies in adults and two in children. In adults, the pooled summary β regression coefficients of the association of PM2.5, PM10 and NO2 with hippocampal volume showed respectively a stronger association (summary β -7.59, 95% CI -14.08 to -1.11), a weaker association (summary β -2.02, 95% CI -4.50 to 0.47), and no association (summary β -0.44, 95% CI -1.27 to 0.40). The two studies available for children, both carried out in preadolescents, did not show an association between PM2.5 and hippocampal volume. The inverse association between PM2.5 and hippocampal volume in adults appeared to be stronger at higher mean PM2.5 levels. Our results suggest that outdoor PM2.5 and less strongly PM10 could adversely affect hippocampal volume in adults, a phenomenon that may explain why air pollution has been related to memory loss, cognitive decline, and dementia

Zinc and selenium supplementation in COVID-19 prevention and treatment: a systematic review of the experimental studies

Background and aim: The COVID-19 pandemic has severely affected the world’s population in the last two years. Along with non-pharmacological public health interventions, major efforts have also been made to identify effective drugs or active substances for COVID-19 prevention and treatment. These include, among many others, the trace elements zinc and selenium, based on laboratory studies and some observational human studies. However, both of these study designs are not adequate to identify and approve treatments in human medicine, and experimental studies in the form of randomized controlled trials are needed to demonstrate the effectiveness and the safety of any interventions. Methods: We undertook a systematic review in which we searched for published and unpublished clinical trials using zinc or selenium supplementation to treat or prevent COVID-19 in the Pubmed, Scopus and ClinicalTrials databases up to January 10th, 2022. Results: Amongst the published studies, we did not find any trial with selenium, whereas we retrieved four eligible randomized clinical trials using zinc supplementation, only one of which was double-blind. One of these trials looked at the effect of the intervention on the rate of new SARS-CoV-2 infections, and three at the COVID-19 clinical outcome in already infected individuals. The study populations of the four trials were very heterogeneous, ranging from uninfected individuals to those hospitalized for COVID-19. Only two studies investigated zinc alone in the intervention arm with no differences in the endpoints. The other two studies examined zinc in association with one or more drugs and supplements in the intervention arm, therefore making it impossible to disentangle any specific effects of the element. In addition, we identified 22 unpublished ongoing clinical trials, 19 on zinc, one on selenium and two on both elements. Conclusion: No trials investigated the effect of selenium supplementation on COVID-19, while the very few studies on the effects of zinc supplementation did not confirm efficacy. Therefore, preventive or therapeutic interventions against COVID-19 based on zinc or selenium supplementation are currently unjustified, although when the results of the on-going studies are published, this may change our conclusion

The association between air pollutants and hippocampal volume from magnetic resonance imaging: A systematic review and meta-analysis

Growing epidemiological evidence suggests that air pollution may increase the risk of cognitive decline and neurodegenerative disease. A hallmark of neurodegeneration and an important diagnostic biomarker is volume reduction of a key brain structure, the hippocampus. We aimed to investigate the possibility that outdoor air nitrogen dioxide (NO2) and particulate matter with diameter ≤2.5 μm (PM2.5) and ≤10 μm (PM10) adversely affect hippocampal volume, through a meta-analysis. We considered studies that assessed the relation between outdoor air pollution and hippocampal volume by structural magnetic resonance imaging in adults and children, searching in Pubmed and Scopus databases from inception through July 13, 2021. For inclusion, studies had to report the correlation coefficient along with its standard error or 95% confidence interval (CI) between air pollutant exposure and hippocampal volume, to use standard space for neuroimages, and to consider at least age, sex and intracranial volume as covariates or effect modifiers. We meta-analyzed the data with a random-effects model, considering separately adult and child populations. We retrieved four eligible studies in adults and two in children. In adults, the pooled summary β regression coefficients of the association of PM2.5, PM10 and NO2 with hippocampal volume showed respectively a stronger association (summary β −7.59, 95% CI −14.08 to −1.11), a weaker association (summary β −2.02, 95% CI −4.50 to 0.47), and no association (summary β −0.44, 95% CI −1.27 to 0.40). The two studies available for children, both carried out in preadolescents, did not show an association between PM2.5 and hippocampal volume. The inverse association between PM2.5 and hippocampal volume in adults appeared to be stronger at higher mean PM2.5 levels. Our results suggest that outdoor PM2.5 and less strongly PM10 could adversely affect hippocampal volume in adults, a phenomenon that may explain why air pollution has been related to memory loss, cognitive decline, and dementia

The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects

Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising results, suggesting that these methods can identify small structural abnormalities of the hippocampus, which are among the earliest and most frequent brain changes associated with Alzheimer disease (AD). However, CNNs typically achieve the highest accuracy on datasets acquired from the same domain as the training dataset. Transfer learning allows domain adaptation through further training on a limited dataset. In this study, we applied transfer learning on a network called spatial warping network segmentation (SWANS), developed and trained in a previous study. We used MR images of patients with clinical diagnoses of mild cognitive impairment (MCI) and AD, segmented by two different raters. By using transfer learning techniques, we developed four new models, using different training methods. Testing was performed using 26% of the original dataset, which was excluded from training as a hold-out test set. In addition, 10% of the overall training dataset was used as a hold-out validation set. Results showed that all the new models achieved better hippocampal segmentation quality than the baseline SWANS model (ps

Association between selenium species and hippocampal volume in subjects with mild cognitive impairment

Background Selenium is a trace element with nutritional and toxicological properties. Its influence on human health is thought to depend on exposure dose and chemical form. The effects of selenium exposure on medical conditions that involve the central nervous system have been insufficiently studied. In a cohort of individuals with mild cognitive impairment, we have previously documented a positive relation between cerebrospinal fluid (CSF) levels of inorganic hexavalent selenium (selenate) and risk of dementia. Methods/Approach We assessed the relation between CSF levels of selenium species and volume of the hippocampus among the 33 cohort members aged 43-82 years who had undergone magnetic resonance imaging at baseline (2008-2014) using both linear and spline regression analyses. We also performed a surface-based analysis using SPHARM-PDM to evaluate differences in shape of the hippocampus in addition to its volume in relation to CSF levels of selenium species. Results We found an inverse association between selenate and total hippocampal volume (β regression coefficient in multivariable linear regression analysis -3.05, 95% confidence interval -5.74 to -0.37), which was similar for the right and left hippocampus and emerged mainly at the highest exposure levels. We found little association between the other selenium forms and hippocampal volume. In the surface-based analysis, the left hippocampus showed considerably more pronounced shape differences in the ventro-medial region of the head. Conclusions This is the first study to analyze selenium species in relation to hippocampal volume and structure, suggesting that a selenium form with high toxicological potential may adversely affect a key structure involved in dementia onset and progression as the hippocampus, possibly the left one in particular. However, we cannot entirely rule out the influence of reverse causation or unmeasured confounding on these results

The influence of meteorological factors on COVID-19 spread in Italy during the first and second wave

: The relation between meteorological factors and COVID-19 spread remains uncertain, particularly with regard to the role of temperature, relative humidity and solar ultraviolet (UV) radiation. To assess this relation, we investigated disease spread within Italy during 2020. The pandemic had a large and early impact in Italy, and during 2020 the effects of vaccination and viral variants had not yet complicated the dynamics. We used non-linear, spline-based Poisson regression of modeled temperature, UV and relative humidity, adjusting for mobility patterns and additional confounders, to estimate daily rates of COVID-19 new cases, hospital and intensive care unit admissions, and deaths during the two waves of the pandemic in Italy during 2020. We found little association between relative humidity and COVID-19 endpoints in both waves, whereas UV radiation above 40&nbsp;kJ/m2 showed a weak inverse association with hospital and ICU admissions in the first wave, and a stronger relation with all COVID-19 endpoints in the second wave. Temperature above 283&nbsp;K (10&nbsp;°C/50&nbsp;°F) showed a strong non-linear negative relation with COVID-19 endpoints, with inconsistent relations below this cutpoint in the two waves. Given the biological plausibility of a relation between temperature and COVID-19, these data add support to the proposition that temperature above 283&nbsp;K, and possibly high levels of solar UV radiation, reduced COVID-19 spread