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Background Low-dose spiral computed tomography (LDCT) may not lead to a clear treatment path when small to intermediate-sized lung nodules are identified. We have combined flow cytometry and machine learning to develop a sputum-based test (CyPath Lung) that can assist physicians in decision-making in such cases. Methods Single cell suspensions prepared from induced sputum samples collected over three consecutive days were labeled with a viability dye to exclude dead cells, antibodies to distinguish cell types, and a porphyrin to label cancer-associated cells. The labeled cell suspension was run on a flow cytometer and the data collected. An analysis pipeline combining automated flow cytometry data processing with machine learning was developed to distinguish cancer from non-cancer samples from 150 patients at high risk of whom 28 had lung cancer. Flow data and patient features were evaluated to identify predictors of lung cancer. Random training and test sets were chosen to evaluate predictive variables iteratively until a robust model was identified. The final model was tested on a second, independent group of 32 samples, including six samples from patients diagnosed with lung cancer. Results Automated analysis combined with machine learning resulted in a predictive model that achieved an area under the ROC curve (AUC) of 0.89 (95% CI 0.83–0.89). The sensitivity and specificity were 82% and 88%, respectively, and the negative and positive predictive values 96% and 61%, respectively. Importantly, the test was 92% sensitive and 87% specific in cases when nodules were Conclusion CyPath Lung correctly classifies samples as cancer or non-cancer with high accuracy, including from participants at different disease stages and with nodules Trial registration ClinicalTrials.gov ID: NCT03457415; March 7, 2018

Studies of charged-particle reactions for low-energy nuclear astrophysics require high sensitivity, which can be achieved by means of detection setups with high efficiency and low backgrounds, to obtain precise measurements in the energy region of interest for stellar scenarios. High-efficiency total absorption spectroscopy is an established and powerful tool for studying radiative capture reactions, particularly if combined with the cosmic background reduction by several orders of magnitude obtained at the Laboratory for Underground Nuclear Astrophysics (LUNA). We present recent improvements in the detection setup with the Bismuth Germanium Oxide (BGO) detector at LUNA, aiming to reduce high-energy backgrounds and increase the summing detection efficiency. The new design results in enhanced sensitivity of the BGO setup, as we demonstrate and discuss in the context of the first direct measurement of the 65 keV resonance (E x = 5672 keV) of the 17O(p,γ)18F reaction. Moreover, we show two applications of the BGO detector, which exploit its segmentation. In the case of complex γ-ray cascades, e.g. the de-excitation of E x = 5672 keV in 18F, the BGO segmentation allows to identify and suppress the beam-induced background signals that mimic the sum peak of interest. We demonstrate another new application for such a detector in form of in situ activation measurements of a reaction with β + unstable product nuclei, e.g. the 14N(p,γ)15O reaction.

Low dose computed tomography (LDCT) is the standard of care for lung cancer screening in the United States (US). LDCT has a sensitivity of 93.8% but its specificity of 73.4% leads to potentially harmful follow-up procedures in patients without lung cancer. Thus, there is a need for additional assays with high accuracy that can be used as an adjunct to LDCT to diagnose lung cancer. Sputum is a biological fluid that can be obtained non-invasively and can be dissociated to release its cellular contents, providing a snapshot of the lung environment. We obtained sputum from current and former smokers with a 30+ pack-year smoking history and who were either confirmed to have lung cancer or at high risk of developing the disease. Dissociated sputum cells were counted, viability determined, and labeled with a panel of markers to separate leukocytes from non-leukocytes. After excluding debris and dead cells, including squamous epithelial cells, we identified reproducible population signatures and confirmed the samples’ lung origin. In addition to leukocyte and epithelial-specific fluorescent antibodies, we used the highly fluorescent meso-tetra(4-carboxyphenyl) porphyrin (TCPP), known to preferentially stain cancer (associated) cells. We looked for differences in cell characteristics, population size and fluorescence intensity that could be useful in distinguishing cancer samples from high-risk samples. We present our data demonstrating the feasibility of a flow cytometry platform to analyze sputum in a high-throughput and standardized matter for the diagnosis of lung cancer.

A recent experiment on 12C + 24Mg sub-barrier fusion was performed. Standard coupled-channels calculations clearly over-estimated the low energy cross sections and there was indication of a maximum of the astrophysical S factor vs energy. In the present work further measurements have been performed on the same system, and we extended the excitation function to lower energies down to σ ≃ 4 μb, confirming the existence of the hindrance phenomenon. Additional energy points near the barrier were added as well. In agreement with the result of previous experiment, the hindrance energy threshold is observed to correspond to a remarkably large cross section. The present new data allow to better define the S-factor maximum, that is well fitted using two parametrizations of either the hindrance or the adiabatic model. We also performed coupled-channels calculations using a Woods–Saxon potential. Far below the barrier we observe that the coupling strengths decrease and tend to vanish, indeed one-dimensional tunnelling calculations well reproduce the excitation function. Further precise cross section measurements at slightly lower energies are needed to discriminate between the adiabatic and hindrance models. This would give a reliable guidance for the extrapolation to the systems of astrophysical interest, like 12C + 12C and 16O + 16O.