Associations between fine particulate matter, gene expression, and promoter methylation in human bronchial epithelial cells exposed within a classroom under air-liquid interface.

Associations between indoor air pollution from fine particulate matter (PM with aerodynamic diameter dp < 2.5 µm) and human health are poorly understood. Here, we analyse the concentration-response curves for fine and ultrafine PM, the gene expression, and the methylation patterns in human bronchial epithelial cells (BEAS-2B) exposed at the air-liquid interface (ALI) within a classroom in downtown Rome. Our results document the upregulation of aryl hydrocarbon receptor (AhR) and genes associated with xenobiotic metabolism (CYP1A1 and CYP1B1) in response to single exposure of cells to fresh urban aerosols at low fine PM mass concentrations within the classroom. This is evidenced by concentrations of ultrafine particles (UFPs, dp < 0.1 µm), polycyclic aromatic hydrocarbons (PAH), and ratios of black carbon (BC) to organic aerosol (OA). Additionally, an interleukin 18 (IL-18) down-regulation was found during periods of high human occupancy. Despite the observed gene expression dysregulation, no changes were detected in the methylation levels of the promoter regions of these genes, indicating that the altered gene expression is not linked to changes in DNA methylation and suggesting the involvement of another epigenetic mechanism in the gene regulation. Gene expression changes at low exposure doses have been previously reported. Here, we add the possibility that lung epithelial cells, when singly exposed to real environmental concentrations of fine PM that translate into ultra-low doses of treatment, may undergo epigenetic alteration in the expression of genes related to xenobiotic metabolism. Our findings provide a perspective for future indoor air quality regulations. We underscore the potential role of indoor UFPs as carriers of toxic molecules with low-pressure weather conditions, when rainfall and strong winds may favour low levels of fine PM.

Interferometric laser imaging for respiratory droplets sizing.

Due to its importance in airborne disease transmission, especially because of the COVID-19 pandemic, much attention has recently been devoted by the scientific community to the analysis of dispersion of particle-laden air clouds ejected by humans during different respiratory activities. In spite of that, a lack of knowledge is still present particularly with regard to the velocity of the emitted particles, which could differ considerably from that of the air phase. The velocity of the particles is also expected to vary with their size. In this work, simultaneous measurements of size and velocity of particles emitted by humans while speaking have been performed by means of Interferometric Laser Imaging Droplet Sizing (ILIDS). This technique allowed us to detect emitted particles with size down to 2 µm as well as to quantify all three components of the velocity vector and the particle concentration. The outcomes of this work may be used as boundary conditions for numerical simulations of infected respiratory cloud transmission.

Application of Artificial Neural Network to Preoperative 18F-FDG PET/CT for Predicting Pathological Nodal Involvement in Non-small-cell Lung Cancer Patients.

Purpose: To evaluate the performance of artificial neural networks (aNN) applied to preoperative 18F-FDG PET/CT for predicting nodal involvement in non-small-cell lung cancer (NSCLC) patients. Methods: We retrospectively analyzed data from 540 clinically resectable NSCLC patients (333 M; 67.4 ± 9 years) undergone preoperative 18F-FDG PET/CT and pulmonary resection with hilo-mediastinal lymphadenectomy. A 3-layers NN model was applied (dataset randomly splitted into 2/3 training and 1/3 testing). Using histopathological reference standard, NN performance for nodal involvement (N0/N+ patient) was calculated by ROC analysis in terms of: area under the curve (AUC), accuracy (ACC), sensitivity (SE), specificity (SP), positive and negative predictive values (PPV, NPV). Diagnostic performance of PET visual analysis (N+ patient: at least one node with uptake ≥ mediastinal blood-pool) and of logistic regression (LR) was evaluated. Results: Histology proved 108/540 (20%) nodal-metastatic patients. Among all collected data, relevant features selected as input parameters were: patients' age, tumor parameters (size, PET visual and semiquantitative features, histotype, grading), PET visual nodal result (patient-based, as N0/N+ and N0/N1/N2). Training and testing NN performance (AUC = 0.849, 0.769): ACC = 80 and 77%; SE = 72 and 58%; SP = 81 and 81%; PPV = 50 and 44%; NPV = 92 and 89%, respectively. Visual PET performance: ACC = 82%, SE = 32%, SP = 94%; PPV = 57%, NPV = 85%. Training and testing LR performance (AUC = 0.795, 0.763): ACC = 75 and 77%; SE = 68 and 55%; SP = 77 and 82%; PPV = 43 and 43%; NPV = 90 and 88%, respectively. Conclusions: aNN application to preoperative 18F-FDG PET/CT provides overall good performance for predicting nodal involvement in NSCLC patients candidate to surgery, especially for ruling out nodal metastases, being NPV the best diagnostic result; a high NPV was also reached by PET qualitative assessment. Moreover, in such population with low a priori nodal involvement probability, aNN better identify the relatively few and unexpected nodal-metastatic patients than PET analysis, so supporting the additional aNN use in case of PET-negative images.

The prognostic role of end-of-treatment FDG-PET/CT in diffuse large B cell lymphoma: a pilot study application of neural networks to predict time-to-event.

PURPOSE: To evaluate the prognostic role of end-of-treatment (EoT) FDG-PET/CT parameters in diffuse large B cell lymphoma (DLBCL), and then to explore a pilot application of Neural Networks (NN) in predicting time-to-relapse. METHODS: For conventional survival analysis, parameters as Deauville score (DS) and quantitative extension of DS (qPET) were correlated to adverse events as relapse or progression in the follow-up. To build NN and conventional multi-regression models (MM) for time-to-event prediction, patients with residual FDG uptake (DS ≥ 2) and an adverse event were divided into a training and a test group. Models developed on the training group were evaluated in the test group. Pearson correlation coefficient (R) and mean relative error between observed and forecasted time-to-event were calculated. RESULTS: FDG-PET/CT data of 308 patients with DLBCL were analyzed. DS and qPET were prognostic factors in conventional univariate analysis. Positive and negative predictive values, respectively, were 55% and 83% for DS 4-5, 89% and 82% for positive qPET. Focusing on 37 relapsed patients with a residual FDG uptake, R between observed and forecasted time-to-event was of 0.63 in the NN model and 0.49 in the MM. Mean relative error in predicting time-to-event was of 58% for NN and 67% for MM. CONCLUSIONS: EoT FDG-PET/CT visual score (DS) is a strong outcome predictor in DLBCL in a large monocentric cohort. The semi-quantitative parameter qPET may increase this prognostic performance. A pilot NN model applied on residual FDG uptake parameters seems to predict time-to-event in the follow-up.

Association between mobile phone traffic volume and road crash fatalities: A population-based case-crossover study.

Use of mobile phones while driving is known to cause crashes with possible fatalities. Different habits of mobile phone use might be distracting forces and display differential impacts on accident risk; the assessment of the relative importance is relevant to implement prevention, mitigation, and control measures. This study aimed to assess the relationship between the use of mobile phones at population level and road crash fatalities in large urban areas. Data on road crashes with fatalities were collected from seven Italian metropolitan areas and matched in time and space with high resolution mobile phone traffic volume data about calls, texts, Internet connections and upload/download data. A case-crossover study design was applied to estimate the relative risks of road accident for increases in each type of mobile phone traffic volumes in underlying population present in the small areas where accidents occurred. Effect modification was evaluated by weekday/weekend, hour of the day, meteorological conditions, and street densities. Positive associations between road crashes rates and the number of calls, texts, and Internet connections were found, with incremental risks of 17.2% (95% Confidence Interval [CI] 7.7, 27.6), 8.4% (CI 0.7, 16.8), and 54.6% (CI 34.0, 78.5) per increases (at 15 min intervals) of 5 calls/100 people, 3 text/100 people, and 40 connections/100 people, respectively. Small differences across cities were detected. Working days, nighttime and morning hours were associated with greater phone use and more road accidents. The relationship between mobile phone use and road fatalities at population level is strong. Strict controls on cellular phone in the vehicle may results in a large health benefit.

Early evaluation of cerebral metabolic rate of glucose (CMRglu) with 18F-FDG PET/CT and clinical assessment in idiopathic normal pressure hydrocephalus (INPH) patients before and after ventricular shunt placement: preliminary experience.

PURPOSE: We evaluated the relationships between the cerebral metabolic rate of glucose (CMRglu) measured by dynamic (18)F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) and the clinical and neuropsychological assessment before and after the surgical procedure in idiopathic normal pressure hydrocephalus (INPH) patients. METHODS: Eleven selected INPH patients underwent clinical assessment (modified Rankin scale, Krauss scale, Larsson categorization system and Stein-Langfitt scale), cognitive evaluation (Mini-Mental State Examination, MMSE) and dynamic (18)F-FDG PET/CT scan 3 days before and 1 week after ventricular shunt placement. RESULTS: After shunting, the global CMRglu significantly increased (2.95 ± 0.44 vs 4.38 ± 0.68, p = 10(-7)) in all INPH patients with a mean percentage value of 48.7%. After shunting, no significant change was found in the Evans ratio whereas a significant decrease in all clinical scale scores was observed. Only a slight reduction in the MMSE was found. After shunting, a significant correlation between the global CMRglu value and clinical assessment was found (R (2) = 0.75, p = 0.024); indeed all clinical scale scores varied (decreasing) and the CMRglu value also varied (increasing) in all INPH patients. CONCLUSION: Our preliminary data show that changes in the CMRglu are promptly reversible after surgery and that there is a relationship between the early metabolic changes and clinical symptoms, independently from the simultaneous changes in the ventricular size. The remarkable and prompt improvement in the global CMRglu and in symptoms may also have important implications for the current concept of "neuronal plasticity" and for the cells' reactivity in order to recover their metabolic function.