Remediation of chlorinated solvents with Electrical Resistance Heating (ERH) at an active industrial site in Italy

Italian legislation defines stringent groundwater chemical quality criteria, to be applied at a site’s downgradient property boundary, irrespective of whether the underlying aquifer is, or could be, used for water resource purposes. In some scenarios, the regulatory authorities may identify less stringent standards, but this rarely occurs. This means that many sites with groundwater contamination are managed using hydraulic barriers, as source zone remediation may not achieve the stringent groundwater standards required due to technology limits or time constraints; therefore, the parties responsible for contamination often decide to continue to operate these hydraulic barriers indefinitely. This article describes the first application in Italy of source treatment using Electrical Resistance Heating (ERH), a remediation technology capable of removing a large percentage of contaminant mass, at a site where a hydraulic barrier is operating within a low yielding aquifer that is not used for water supply. The implementation of this technology was possible since the source zone was far from the downgradient site boundary, thus making achievement of the stringent quality standards at the boundary possible within a reasonable timeframe. The ERH system recovered of about 600 kg of contaminants within a timeframe of 8 months and achieved a reduction of contaminant concentrations in the most impacted areas greater than 90%. This article also emphasizes that, in similar low yielding aquifers, setting less stringent groundwater standards at the site boundary whilst still protecting downgradient receptors may promote more widespread implementation of source remediation activities in Italy

Reirradiation of head and neck squamous cell carcinomas: a pragmatic approach-part I: prognostic factors and indications to treatment.

INTRODUCTION Reirradiation (reRT) of locally recurrent/second primary tumors of the head and neck region is a potentially curative treatment for patients not candidate to salvage surgery. Aim of the present study is to summarize available literature on both prognostic factors and indications to curative reRT in this clinical setting. MATERIALS AND METHODS A narrative review of the literature was performed on two topics: (1) patients' selection according to prognostic factors and (2) dosimetric feasibility of reRT. Postoperative reRT and palliative intent treatments were out of the scope of this work. RESULTS Patient-tumor and treatment-related prognostic factors were analyzed, together with dosimetric parameters concerning target volume and organs at risk. Based on available evidence, a stepwise approach has been proposed aiming to provide a useful tool to identify suitable candidates for curative reRT in clinical practice. This was then applied to two clinical cases, proposed at the end of this work. CONCLUSION A second course of RT in head and neck recurrence/second primary tumors is a personalized approach that can be offered to selected patients only in centers with expertise and dedicated equipment following a multidisciplinary team discussion

Impact of image filtering and assessment of volume-confounding effects on CT radiomic features and derived survival models in non-small cell lung cancer

BACKGROUND No evidence supports the choice of specific imaging filtering methodologies in radiomics. As the volume of the primary tumor is a well-recognized prognosticator, our purpose is to assess how filtering may impact the feature/volume dependency in computed tomography (CT) images of non-small cell lung cancer (NSCLC), and if such impact translates into differences in the performance of survival modeling. The role of lesion volume in model performances was also considered and discussed. METHODS Four-hundred seventeen CT images NSCLC patients were retrieved from the NSCLC-Radiomics public repository. Pre-processing and features extraction were implemented using Pyradiomics v3.0.1. Features showing high correlation with volume across original and filtered images were excluded. Cox proportional hazards (PH) with least absolute shrinkage and selection operator (LASSO) regularization and CatBoost models were built with and without volume, and their concordance (C-) indices were compared using Wilcoxon signed-ranked test. The Mann Whitney U test was used to assess model performances after stratification into two groups based on low- and high-volume lesions. RESULTS Radiomic models significantly outperformed models built on only clinical variables and volume. However, the exclusion/inclusion of volume did not generally alter the performances of radiomic models. Overall, performances were not substantially affected by the choice of either imaging filter (overall C-index 0.539-0.590 for Cox PH and 0.589-0.612 for CatBoost). The separation of patients with high-volume lesions resulted in significantly better performances in 2/10 and 7/10 cases for Cox PH and CatBoost models, respectively. Both low- and high-volume models performed significantly better with the inclusion of radiomic features (P<0.0001), but the improvement was largest in the high-volume group (+10.2% against +8.7% improvement for CatBoost models and +10.0% against +5.4% in Cox PH models). CONCLUSIONS Radiomic features complement well-known prognostic factors such as volume, but their volume-dependency is high and should be managed with vigilance. The informative content of radiomic features may be diminished in small lesion volumes, which could limit the applicability of radiomics in early-stage NSCLC, where tumors tend to be small. Our results also suggest an advantage of CatBoost models over the Cox PH models

Applications of Isothermal Titration Calorimetry in Biophysical Studies of G-quadruplexes

G-quadruplexes are higher-order nucleic acids structures formed by G-rich sequences that are stabilized by tetrads of hydrogen-bonded guanine bases. Recently, there has been growing interest in the study of G-quadruplexes because of their possible involvement in many biological processes. Isothermal titration calorimetry (ITC) has been proven to be a useful tool to study the energetic aspects of G-quadruplex interactions. Particularly, ITC has been applied many times to determine the thermodynamic properties of drug-quadruplex interactions to screening among various drugs and to address drug design. In the present review, we will focus on the ITC studies of G-quadruplex structures and their interaction with proteins and drugs and the most significant results will be discussed

Quality assurance for automatically generated contours with additional deep learning

Objective: Deploying an automatic segmentation model in practice should require rigorous quality assurance (QA) and continuous monitoring of the model’s use and performance, particularly in high-stakes scenarios such as healthcare. Currently, however, tools to assist with QA for such models are not available to AI researchers. In this work, we build a deep learning model that estimates the quality of automatically generated contours. Methods: The model was trained to predict the segmentation quality by outputting an estimate of the Dice similarity coefficient given an image contour pair as input. Our dataset contained 60 axial T2-weighted MRI images of prostates with ground truth segmentations along with 80 automatically generated segmentation masks. The model we used was a 3D version of the EfficientDet architecture with a custom regression head. For validation, we used a fivefold cross-validation. To counteract the limitation of the small dataset, we used an extensive data augmentation scheme capable of producing virtually infinite training samples from a single ground truth label mask. In addition, we compared the results against a baseline model that only uses clinical variables for its predictions. Results: Our model achieved a mean absolute error of 0.020 ± 0.026 (2.2% mean percentage error) in estimating the Dice score, with a rank correlation of 0.42. Furthermore, the model managed to correctly identify incorrect segmentations (defined in terms of acceptable/unacceptable) 99.6% of the time. Conclusion: We believe that the trained model can be used alongside automatic segmentation tools to ensure quality and thus allow intervention to prevent undesired segmentation behavior

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and objectives: It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19-related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population. Methods: Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score &gt; 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ2 test, and the risk excess was quantified by risk ratios (RRs). Results: The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p &lt; 0.001), RR = 2.19 for ICU admission (p &lt; 0.001), and RR = 2.43 for death (p &lt; 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04). Discussion: Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR&nbsp;=&nbsp;2.05, 95%CI&nbsp;=&nbsp;1.39–3.02, p&nbsp;&lt;&nbsp;0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR&nbsp;=&nbsp;0.42, 95%CI&nbsp;=&nbsp;0.18–0.99, p&nbsp;=&nbsp;0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

High Resolution Site Characterization as key element for proper design and cost estimation of groundwater remediation

Substantial amounts of money are spent each year on cleaning up ground water contaminations that were caused by historical industrial site activities. Too often, however, remedial objectives are not achieved within the anticipated time frame. Moreover, remedial budgets which were estimated prior to the start of remediation turn out to be largely insufficient to meet the remedial objectives. This situation, very common, creates significant troubles for all the stakeholders involved in the remediation project. The reason for not meeting remedial regulatory closure criteria or exceeding remedial budgets is often due to an incomplete conceptual site model. Having conducted high resolution site characterization programs at numerous sites where remediation was previously conducted, ERM has found several recurring themes: • Missed source areas and plumes; • Inadequate understanding of source area and plume architectures (i.e., three-dimensional contaminant distribution); • Inadequate understanding of the effects of site (hydro)geologic conditions on the ability to access contamination (i.e., via remedial additive injections of groundwater/soil gas extraction). This paper explains why remediations often fail and what the alternatives to prevent these failures (and exceeding remedial budgets) are. More specifically, it focuses on alternative investigation methods and approaches that help to get to a more complete (high resolution) conceptual site model. This more complete conceptual site model in return helps a more focused remedial design with a higher remedial efficiency. As a minimum, it will take away a lot of (financial) uncertainty during the decision making when selecting a remedial alternative. Contaminants that have a greater density then water are known to have a greater complexity in terms of both investigation as well as remediation. Therefore, they will be the main focus of this paper