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In December 2019, a number of subjects presenting with an unexplained pneumonia-like illness were suspected to have a link to a seafood market in Wuhan, China. Subsequently, this illness was identified as the 2019-novel coronavirus (2019-nCoV) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the World Committee on Virus Classification. Since its initial identification, the virus has rapidly sperad across the globe, posing an extraordinary challenge for the medical community. Currently, the Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) is considered the most reliable method for diagnosing SARS-CoV-2. This procedure involves collecting oro-pharyngeal or nasopharyngeal swabs from individuals. Nevertheless, for the early detection of low viral loads, a more sensitive technique, such as droplet digital PCR (ddPCR), has been suggested. Despite the high effectiveness of RT-PCR, there is increasing interest in utilizing highly trained dogs and electronic noses (eNoses) as alternative methods for screening asymptomatic individuals for SARS-CoV-2. These dogs and eNoses have demonstrated high sensitivity and can detect volatile organic compounds (VOCs), enabling them to distinguish between COVID-19 positive and negative individuals. This manuscript recapitulates the potential, advantages, and limitations of employing trained dogs and eNoses for the screening and control of SARS-CoV-2.

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Waste treatment plants (WTPs) often generate odours that may cause nuisance to citizens living nearby. In general, people are becoming more sensitive to environmental issues, and particularly to odour pollution. Instrumental Odour Monitoring Systems (IOMSs) represent an emerging tool for continuous odour measurement and real-time identification of odour peaks, which can provide useful information about the process operation and indicate the occurrence of anomalous conditions likely to cause odour events in the surrounding territories. This paper describes the implementation of two IOMSs at the fenceline of a WTP, focusing on the definition of a specific experimental protocol and data processing procedure for dealing with the interferences of humidity and temperature affecting sensors' responses. Different approaches for data processing were compared and the optimal one was selected based on field performance testing. The humidity compensation model developed proved to be effective, bringing the IOMS classification accuracy above 95%. Also, the adoption of a class-specific regression model compared to a global regression model resulted in an odour quantification capability comparable with those of the reference method (i.e., dynamic olfactometry). Lastly, the validated models were used to process the monitoring data over a period of about one year.

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The real-world, retrospective, NEROnE registry investigated the impact of next-generation sequencing (NGS) in advanced non-small-cell lung cancer (NSCLC) patients (pts) at three oncology units in the north of Italy between January 2020 and December 2022. We focused on the clinical characterization and outcomes of NSCLC with rare molecular alterations: EGFR exon 20 insertion, non-activating EGFR mutations, BRAF V600E and non-V600, ROS1 and RET rearrangements, MET, ErbB2, and FGFR mutations. Overall, these represented 6.4% (62/970) of the pts analysed with NGS in the daily practice. The most heavily represented rare alterations were ROS1 rearrangement (15 pts-24%) and MET exon 14 skipping mutation (11 pts-18%). No associations were found with the demographic and clinical features. Forty-nine pts received targeted therapies, of which 38.8% were first- and 9.8% were second-line. The remaining pts received chemotherapy and/or immunotherapy. In terms of the clinical outcomes, although not statistically significant, a tendency toward shorter OS was seen when therapies other than specific targeted therapies were used (HR: 1.84, 95% CI: 0.79-4.33, p = 0.158). The pts with co-mutations (19.4%) seemed to receive an advantage from the front-line chemotherapy-based regimen. Finally, an NLR score (a well-known inflammatory index) ≥ 4 seemed to be related to shorter OS among the pts treated with immunotherapy alone or in combination with chemotherapy (HR: 2.83, 95% CI: 1.08-7.40, p = 0.033). Prospective evaluations need to be performed to clarify whether these indexes may help to identify patients with oncogene-addicted NSCLC who could benefit from immunotherapy.

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In recent years, electronic noses, or more generally Instrumental Odor Monitoring Systems (IOMS), have aroused increasing interest in the field of environmental monitoring. One of the most interesting applications of these instruments is the real-time estimation of the odor concentration at plant fencelines to continuously monitor odor emissions and identify anomalous conditions. In this type of application, it is possible to setting a "warning" threshold, enabling the continuous check of proper functioning of the plant and sudden intervention in case of malfunctions, preventing, at the same time, the risk of odor events at the receptors. For this purpose, it is necessary to provide a continuous, fast and reliable measurement of the odor concentration, which is nowadays one of the main challenges of this technology. In this context, this work proposes the development of a quantification model for quantifying odors detected at the fenceline of a landfill characterized by very different odor fingerprints. A double-step quantification model, firstly identifying the different odor classes to which the ambient air monitored at the fenceline by the IOMS belong to, and then developing different specific PLS regression models for each of the odor classes identified, was developed. The results of the proposed quantification model were compared to the ones obtained developing a "global" quantification model, which implements the regression on the globality of the training set, without differentiating between the odor classes. Then, they were further evaluated by comparison with the odor events detected at the sensitive receptor by another electronic nose. Moreover, the combined evaluation of the odor events at the plant fenceline and the receptor, respectively, together with the meteorological data highlighted the need of identifying variable warning thresholds for the odor concentrations at the fenceline according to effectively account for meteorological conditions and produce an output that is more correlated with the probability that an odor is perceived outside of the plant.

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Introduction: Prostate cancer (PCa) is known for its highly diverse clinical behavior, ranging from low-risk, slow-growing tumors to aggressive and life-threatening forms. To avoid over-treatment of low-risk PCa patients, it would be very important prior to any therapeutic intervention to appropriately classify subjects based on tumor aggressiveness. Unfortunately, there is currently no reliable test available for this purpose. The aim of the present study was to evaluate the ability of risk stratification of PCa subjects using an electronic nose (eNose) detecting PCa-specific volatile organic compounds (VOCs) in urine samples. Methods: The study involved 120 participants who underwent diagnostic prostate biopsy followed by robot assisted radical prostatectomy (RARP). PCa risk was categorized as low, intermediate, or high based on the D'Amico risk classification and the pathological grade (PG) assessed after RARP. The eNose's ability to categorize subjects for PCa risk stratification was evaluated based on accuracy and recall metrics. Results: The study population comprised 120 participants. When comparing eNose predictions with PG an accuracy of 79.2% (95%CI 70.8 - 86%) was found, while an accuracy of 74.2% (95%CI 65.4 - 81.7%) was found when compared to D'Amico risk classification system. Additionally, if compared low- versus -intermediate-/high-risk PCa, the eNose achieved an accuracy of 87.5% (95%CI 80.2-92.8%) based on PG or 90.8% (95%CI 84.2-95.3%) based on D'Amico risk classification. However, when using low-/-intermediate versus -high-risk PCa for PG, the accuracy was found to be 91.7% (95%CI 85.2-95.9%). Finally, an accuracy of 80.8% (95%CI72.6-87.4%) was found when compared with D'Amico risk classification. Discussion: The findings of this study indicate that eNose may represent a valid alternative not only for early and non-invasive diagnosis of PCa, but also to categorize patients based on tumor aggressiveness. Further studies including a wider sample population will be necessary to confirm the potential clinical impact of this new technology.

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INTRODUCTION: Biomarker testing is mandatory for the clinical management of patients with advanced non-small cell lung cancer (NSCLC). Myriads of technical platforms are now available for biomarker analysis with differences in terms of multiplexing capability, analytical sensitivity, and turnaround time (TAT). We evaluated the technical performance of the diagnostic workflows of 24 representative Italian institutions performing molecular tests on a series of artificial reference specimens built to mimic routine diagnostic samples. METHODS: Sample sets of eight slides from cell blocks of artificial reference specimens harboring exon 19 EGFR (epidermal growth factor receptor) p.E746_AT50del, exon 2 KRAS (Kirsten rat sarcoma viral oncogene homologue) p.G12C, ROS1 (c-ros oncogene 1)-unknown gene fusion, and MET (MET proto-oncogene, receptor tyrosine kinase) Δ exon 14 skipping were distributed to each participating institution. Two independent cell block specimens were validated by the University of Naples Federico II before shipment. Methodological and molecular data from reference specimens were annotated. RESULTS: Overall, a median DNA concentration of 3.3 ng/µL (range 0.1-10.0 ng/µL) and 13.4 ng/µL (range 2.0-45.8 ng/µL) were obtained with automated and manual technical procedures, respectively. RNA concentrations of 5.7 ng/µL (range 0.2-11.9 ng/µL) and 9.3 ng/µL (range 0.5-18.0 ng/µL) were also detected. KRAS exon 2 p.G12C, EGFR exon 19 p.E736_A750del hotspot mutations, and ROS1 aberrant transcripts were identified in all tested cases, whereas 15 out of 16 (93.7%) centers detected MET exon 14 skipping mutation. CONCLUSIONS: Optimized technical workflows are crucial in the decision-making strategy of patients with NSCLC. Artificial reference specimens enable optimization of diagnostic workflows for predictive molecular analysis in routine clinical practice.

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(1) Background: BRAF mutations affect 4-5% of lung adenocarcinomas. This study aimed to analyze the clinicopathological features of lung carcinomas with BRAF mutations, focusing on V600E vs. non-V600E and the presence of co-mutations. (2) Methods: All BRAF-mutated lung carcinomas were retrieved from a molecular diagnostic unit (the reference unit for four different hospitals). The samples were analyzed using next-generation sequencing. Statistical analyses included log-rank tests for overall survival (OS) and progression-free survival (PFS). (3) Results: In total, 60 BRAF-mutated lung carcinomas were retrieved: 24 (40.0%) with V600E and 36 (60.0%) with non-V600E mutations, and 21 (35.0%) with other co-mutations and 39 (65.0%) with only BRAF mutations. Survival data were available for 54/60 (90.0%) cases. Targeted therapy was documented in 11 cases. Patients with V600E mutations exhibited a better prognosis than patients with non-V600E mutations (p = 0.008 for OS, p = 0.018 for PFS); this was confirmed in PFS (p = 0.036) when considering only patients who received no targeted therapy. Patients with co-mutations displayed no prognostic difference compared to patients carrying only BRAF mutations (p = 0.590 for OS, p = 0.938 for PFS). (4) Conclusions: BRAF-mutated lung carcinomas with V600E (40.0%) had a better prognosis than those without V600E. Concomitant co-mutations (35.0%) did not affect the prognosis.

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This paper proposes a novel approach for the real-time monitoring of odour emissions from a WasteWater Treatment Plant (WWTP) using an Instrumental Odour Monitoring System (IOMS). The plant is characterized by unpredictable odour peaks at its arrival tank (AT), generating nuisance and complaints in the population living nearby the plant. Odour peaks are most likely due to the conferment of non-identified and malodorous wastewaters coming from various industrial activities. Due to the high variability of sources collecting their wastewaters to the WWTP, a new methodology to train the IOMS, based on the use of a one-class classifier (OCC), has been exploited. The OCC enables to detect deviations from a "Normal Operating Region" (NOR), defined as to include odour concentrations levels unlikely to cause nuisance in the citizenship. Such deviations from the NOR thus should be representative of the odour peaks. The results obtained prove that the IOMS is able to detect real-time alterations of odour emissions from the AT with an accuracy on independent validation data of about 90% (CI95% 55-100%). This ability of detecting anomalous conditions at the AT of the WWTP allowed the targeted withdrawal of liquid and gas samples in correspondence of the odour peaks, then subjected to further analyses that in turn enabled to investigate their origin and take proper counteractions to mitigate the WWTP odour impact.

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Background: Polymorphous adenocarcinoma (PAC) represents the second most widespread neoplasm of the minor salivary glands. These tumors rarely develop a histological progression from low-grade to high-grade malignancy, named "high-grade transformation" (HGT). Only nine cases are described in literature. Case description: Here, we describe the case of a 76-year-old male patient with a PAC recurrence of the oral floor displaying HGT, and we explore the tumor cytomorphological features, genomic profiling, and the patient's clinical management. The tumor mass was characterized by poorly atypical cellular elements with vesicular nuclei and comedonecrosis foci. The growth pattern was predominantly solid, tubular, and cribriform. The lesion did not show microsatellite instability or targeted molecular alterations. The case was successfully treated with radical surgery followed by radiotherapy. Conclusion: We report for the first time the recurrence of a PAC with HGT arising in the oral floor after 20 years from the primary lesion. These preliminary data and the literature analysis enhance the knowledge of this extremely rare disease.

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PURPOSE: Plasma circulating tumor DNA (ctDNA) is a valuable resource for tumor characterization and for monitoring of residual disease during treatment; however, it is not yet introduced in metastatic colorectal cancer (mCRC) routine clinical practice. In this retrospective exploratory study, we evaluated the role of ctDNA in patients with mCRC treated with chemotherapy plus bevacizumab. MATERIALS AND METHODS: Fifty-three patients were characterized for RAS and BRAF status on tumor tissue before the start of treatment. Plasma was collected at baseline, at first clinical evaluation, and at disease progression. ctDNA analysis was performed using Oncomine Colon cfDNA Assay on the Ion S5 XL instrument. RESULTS: At baseline, from a plasma sample, RAS, BRAF, or PIK3CA mutations were detected in 44 patients. A high correspondence was observed between ctDNA and tumor tissue mutations (KRAS 100%, NRAS 97.9%, BRAF 97.9%, PIK3CA 90%). Low baseline variant allele frequency (VAF) was found to be associated with longer median progression-free survival (PFS) compared with those with high VAF (15.9 v 12.2 months, P = .02). A higher PFS {12.29 months (95% CI, 9.03 to 17.9) v 8.15 months (95% CI, 2.76 to not available [NA]), P = .04} and overall survival (34.1 months [95% CI, 21.68 to NA] v 11.1 months [95% CI, 3.71 to NA], P = .003) were observed in patients with large decline in VAF at first evaluation. CONCLUSION: ctDNA analysis is useful for molecular characterization and tumor response monitoring in patients with mCRC. Quantitative variations of released ctDNA are associated with clinical outcomes.

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Odors are typically released into the atmosphere as diffuse emissions from area and volume sources, whose detailed quantification in terms of odor emission rate is often hardly achievable by direct source sampling. Indirect methods, involving the use of micrometeorological methods in order to correlate downwind concentrations to the emission rates, are already mentioned in literature, but rarely found in real applications for the quantification of odor emissions. The instrumentation needed for the development of micrometeorological methods has nowadays become accessible in terms of prices and reliability, thus making the implementation of such methods to industrial applications more and more interesting. For this reason, this work aims to provide an overview of micrometeorological methods and investigate their effective applicability to odors, thereby providing a short description of the physics related to such methods and analyzing the relevant scientific literature. The theoretical basis of these methods is presented, and their advantages and disadvantages are discussed. Moreover, their applicability to the estimation of odor emissions is discussed by providing some suggestions about the suitable ways to evaluate the most critical parameters needed for the calculation of the odor emission rate.

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OBJECTIVE: To evaluate the accuracy of a new electronic nose to recognize prostate cancer in urine samples. METHODS: A blind, prospective study on consecutive patients was designed. Overall, 174 subjects were included in the study: 88 (50.6%) in prostate cancer group, and 86 (49.4%) in control group. Electronic nose performance for prostate cancer was assessed using sensitivity and specificity. The diagnostic accuracy of electronic nose was reported as area under the receiver operating characteristic curve. RESULTS: The electronic nose in the study population reached a sensitivity 85.2% (95% confidence interval 76.1-91.9; 13 false negatives out of 88), a specificity 79.1% (95% confidence interval 69.0-87.1; 18 false positives out of 86). The accuracy of the electronic nose represented as area under the receiver operating characteristic curve 0.821 (95% confidence interval 0.764-0.879). CONCLUSIONS: The diagnostic accuracy of electronic nose for recognizing prostate cancer in urine samples is high, promising and susceptible to supplemental improvement. Additionally, further studies will be necessary to design a clinical trial to validate electronic nose application in diagnostic prostate cancer nomograms.

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Background: Non-invasive, bedside diagnostic tools are extremely important for tailo ring the management of respiratory failure patients. The use of electronic noses (ENs) for exhaled breath analysis has the potential to provide useful information for phenotyping different respiratory disorders and improving diagnosis, but their application in respiratory failure patients remains a challenge. We developed a novel measurement apparatus for analysing exhaled breath in such patients. Methods: The breath sampling apparatus uses hospital medical air and oxygen pipeline systems to control the fraction of inspired oxygen and prevent contamination of exhaled gas from ambient Volatile Organic Compounds (VOCs) It is designed to minimise the dead space and respiratory load imposed on patients. Breath odour fingerprints were assessed using a commercial EN with custom MOX sensors. We carried out a feasibility study on 33 SARS-CoV-2 patients (25 with respiratory failure and 8 asymptomatic) and 22 controls to gather data on tolerability and for a preliminary assessment of sensitivity and specificity. The most significant features for the discrimination between breath-odour fingerprints from respiratory failure patients and controls were identified using the Boruta algorithm and then implemented in the development of a support vector machine (SVM) classification model. Results: The novel sampling system was well-tolerated by all patients. The SVM differentiated between respiratory failure patients and controls with an accuracy of 0.81 (area under the ROC curve) and a sensitivity and specificity of 0.920 and 0.682, respectively. The selected features were significantly different in SARS-CoV-2 patients with respiratory failure versus controls and asymptomatic SARS-CoV-2 patients (p < 0.001 and 0.046, respectively). Conclusions: the developed system is suitable for the collection of exhaled breath samples from respiratory failure patients. Our preliminary results suggest that breath-odour fingerprints may be sensitive markers of lung disease severity and aetiology.

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Endometriosis is a benign condition characterized by the presence of ectopic endometrial tissue. It is still debated whether endometriosis is a disease that can predispose to the pathogenesis of endometrial cancer outside the uterus. Deficiencies in mismatch repair (MMR) genes are a known risk factor for developing endometrioid cancer. Starting from two cases of patients with abnormal MMR endometrioid carcinoma of the uterus and synchronous endometrioid carcinoma in non-ovarian and ovarian endometriosis, we performed a somatic mutation profile and phylogenetic analysis of the lesions in order to identify if they were metastasis or primary de novo tumors. In the first case, we identified de novo activating mutations in PIK3CA and KRAS in endometrioid cancer lesions but not in endometriosis. Although the acquisition of a de novo mutation in ESR1 and a decrease in mutant allele fraction (MAF) from the endometrial tumor to the localizations in the endometriosis lesions, the clonal relationship was confirmed by the limited number of heteroplasmic mutations in D-loop mitochondrial DNA region. In the other case, the clonal behavior was demonstrated by the overlap of MAF at each site. Our data support the hypothesis of a retrograde dissemination of tumor cells, moving from the primary carcinoma in the endometrium to ectopic sites of endometriosis where localizations of tumor arise.

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AIMS: Next-generation sequencing (NGS) is becoming a new gold standard for determining molecular predictive biomarkers. This study aimed to evaluate the reliability of NGS in detecting gene fusions, focusing on comparing gene fusions with known and unknown partners. METHODS: We collected all gene fusions from a consecutive case series using an amplicon-based DNA/RNA NGS platform and subdivided them into two groups: gene fusions with known partners and gene fusions with unknown partners. Gene fusions involving ALK, ROS1 and RET were also examined by immunohistochemistry (IHC) and/or fluorescent in situ hybridization (FISH). RESULTS: Overall, 1174 malignancies underwent NGS analysis. NGS detected gene fusions in 67 cases (5.7%), further subdivided into 43 (64.2%) with known partners and 24 (35.8%) with unknown partners. Gene fusions were predominantly found in non-small cell lung carcinomas (52/67, 77.6%). Gene fusions with known partners frequently involved ALK (20/43, 46.5%) and MET (9/43, 20.9%), while gene fusions with unknown partners mostly involved RET (18/24, 75.0%). FISH/IHC confirmed rearrangement status in most (89.3%) of the gene fusions with known partners, but in only one (4.8%) of the gene fusions with unknown partners, with a significant difference (p < 0.001). In 17 patients undergoing targeted therapy, the log-rank test revealed that the overall survival was higher in the known partner group than in the unknown partner group (p = 0.002). CONCLUSIONS: NGS is a reliable method for detecting gene fusions with known partners, but it is less accurate in identifying gene fusions with unknown partners, for which further analyses (such as FISH) are required.

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Diagnostic protocol for prostate cancer (KP) is affected by poor accuracy and high false-positive rate. The most promising innovative approach is based on urine analysis by electronic noses (ENs), highlighting a specific correlation between urine alteration and KP presence. Although EN could be exploited to develop non-invasive KP diagnostic tools, no study has already introduced EN into clinical practice, most probably because of drift issues that hinder EN scaling up from research objects to large-scale diagnostic devices. This study, proposing an EN for non-invasive KP detection, describes the data processing protocol applied to a urine headspace dataset acquired over 9 months, comprising 81 patients with KP and 41 controls, for compensating the drift. It proved effective in mitigating drift on 1-year-old sensors by restoring accuracy from 55% up to 80%, achieved by new sensors not subjected to drift. The model achieved, on double-blind validation, a balanced accuracy of 76.2% (CI95% 51.9-92.3).

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More than one million new cases of prostate cancer (PCa) were reported worldwide in 2020, and a significant increase of PCa incidence up to 2040 is estimated. Despite potential treatability in early stages, PCa diagnosis is challenging because of late symptoms' onset and limits of current screening procedures. It has been now accepted that cell transformation leads to release of volatile organic compounds in biologic fluids, including urine. Thus, several studies proposed the possibility to develop new diagnostic tools based on urine analysis. Among these, electronic noses (eNoses) represent one of the most promising devices, because of their potential to provide a non-invasive diagnosis. Here we describe the approach aimed at defining the experimental protocol for eNose application for PCa diagnosis. Our research investigates effects of sample preparation and analysis on eNose responses and repeatability. The dependence of eNose diagnostic performance on urine portion analysed, techniques involved for extracting urine volatiles and conditioning temperature were analysed. 192 subjects (132 PCa patients and 60 controls) were involved. The developed experimental protocol has resulted in accuracy, sensitivity and specificity of 83% (CI95% 77-89), 82% (CI95% 73-88) and 87% (CI95% 75-94), respectively. Our findings define eNoses as valuable diagnostic tool allowing rapid and non-invasive PCa diagnosis.

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BACKGROUND: Liquid biopsy analysis for EGFR detection in cell-free DNA (cfDNA) from NSCLC patients has become routine. The aim of this study was to explore its applicability in clinical practice. METHODS: We collected data of EGFR-mutated NSCLC patients with liquid biopsy analysis. Data included test timing, concomitant tissue re-biopsy, therapy change, histology, stage, smoking habits, gender and age. All analyses were performed via a real-time PCR method to analyze EGFR mutations at exons 18, 19, 20 and 21. Variant allele frequency was performed for patients with available sequential EGFR mutation analysis in cfDNA. Overall survival was analyzed through the Kaplan-Meier method. We designed flow charts to show the real-life application of liquid biopsy. RESULTS: We found that liquid biopsy is used in treatment-naïve patients as an alternative to EGFR detection in tumor tissue, and in patients with positive or negative EGFR from tumor biopsy. The majority of liquid biopsy analyses were performed in NSCLC patients who were disease progressive during TKI therapy. The presence of EGFR mutation in cfDNA was associated with a worse prognosis. In two patients, VAF of EGFR mutations in cfDNA was concordant with tumor volume changes. CONCLUSION: These findings suggest that liquid biopsy for EGFR detection can continue to be useful.

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BACKGROUND: Storage tanks in oil and gas processing facilities contain large volumes of flammable compounds. Once the fuel-air mixture is ignited, it may break out into a large fire or explosion. The growing interest in monitoring air quality and assessing health risks makes the evaluation of the consequences of a fire an important issue. Atmospheric dispersion models, which allow for simulation of the spatial distribution of pollutants, represent an increasingly widespread tool for this type of evaluations. OBJECTIVES: The present study discusses the set up and results of a modeling study relevant to a hypothesized fire in an oil refinery. METHODS: After choosing the most suitable dispersion models, i.e. the Lagrangian model SPRAY and the puff model CALPUFF, estimation of the required input data is discussed, focusing on the source variables, which represent the most uncertain input data. The results of the simulations were compared to regulatory limits to effectively evaluate the environmental consequences. Finally, a sensitivity analysis was employed to identify the most influential variables. RESULTS: The simulation results revealed that ground concentration values were far below the cited long-term limits. However, the most interesting outcome is that depending on the dispersion model and the source type modeled, different results may be obtained. In addition, the sensitivity study indicates that the source area is the most critical variable, since it determines a significantly different behavior depending on the modeled source types, producing, in some cases, variability in the pollutant ground concentrations on selected receptors up to +/- 60%. CONCLUSIONS: Depending on the selected model and the algorithms available to describe the physics of emission, the results showed a different sensitivity to the input variables. Although this can be explained from a mathematical point of view, the problem remains of choosing case by case the option that best approximates the real behavior of the incidental source under investigation. COMPETING INTERESTS: The authors declare no competing financial interests.