65 research outputs found

    Optical nanofibers and spectroscopy

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    We review our recent progress in the production and characterization of tapered optical fibers with a sub-wavelength diameter waist. Such fibers exhibit a pronounced evanescent field and are therefore a useful tool for highly sensitive evanescent wave spectroscopy of adsorbates on the fiber waist or of the medium surrounding. We use a carefully designed flame pulling process that allows us to realize preset fiber diameter profiles. In order to determine the waist diameter and to verify the fiber profile, we employ scanning electron microscope measurements and a novel accurate in situ optical method based on harmonic generation. We use our fibers for linear and non-linear absorption and fluorescence spectroscopy of surface-adsorbed organic molecules and investigate their agglomeration dynamics. Furthermore, we apply our spectroscopic method to quantum dots on the surface of the fiber waist and to caesium vapor surrounding the fiber. Finally, towards dispersive measurements, we present our first results on building and testing a single-fiber bi-modal interferometer.Comment: 13 pages, 18 figures. Accepted for publication in Applied Physics B. Changes according to referee suggestions: changed title, clarification of some points in the text, added references, replacement of Figure 13

    Measurement of the ttbar Production Cross Section in ppbar collisions at sqrt s = 1.96 TeV in the All Hadronic Decay Mode

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    We report a measurement of the ttbar production cross section using the CDF-II detector at the Fermilab Tevatron. The analysis is performed using 311 pb-1 of ppbar collisions at sqrt(s)=1.96 TeV. The data consist of events selected with six or more hadronic jets with additional kinematic requirements. At least one of these jets must be identified as a b-quark jet by the reconstruction of a secondary vertex. The cross section is measured to be sigma(tbart)=7.5+-2.1(stat.)+3.3-2.2(syst.)+0.5-0.4(lumi.) pb, which is consistent with the standard model prediction.Comment: By CDF collaboratio

    Measurement of the W+W- Production Cross Section in ppbar Collisions at sqrt(s)=1.96 TeV using Dilepton Events

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    We present a measurement of the W+W- production cross section using 184/pb of ppbar collisions at a center-of-mass energy of 1.96 TeV collected with the Collider Detector at Fermilab. Using the dilepton decay channel W+W- -> l+l-vvbar, where the charged leptons can be either electrons or muons, we find 17 candidate events compared to an expected background of 5.0+2.2-0.8 events. The resulting W+W- production cross section measurement of sigma(ppbar -> W+W-) = 14.6 +5.8 -5.1 (stat) +1.8 -3.0 (syst) +-0.9 (lum) pb agrees well with the Standard Model expectation.Comment: 8 pages, 2 figures, 2 tables. To be submitted to Physical Review Letter

    Thermodynamic Properties of Methanol in the Critical and Supercritical Regions

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    The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma

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    The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma

    Evolutionary characterization of lung adenocarcinoma morphology in TRACERx

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    Lung adenocarcinomas (LUADs) display a broad histological spectrum from low-grade lepidic tumors through to mid-grade acinar and papillary and high-grade solid, cribriform and micropapillary tumors. How morphology reflects tumor evolution and disease progression is poorly understood. Whole-exome sequencing data generated from 805 primary tumor regions and 121 paired metastatic samples across 248 LUADs from the TRACERx 421 cohort, together with RNA-sequencing data from 463 primary tumor regions, were integrated with detailed whole-tumor and regional histopathological analysis. Tumors with predominantly high-grade patterns showed increased chromosomal complexity, with higher burden of loss of heterozygosity and subclonal somatic copy number alterations. Individual regions in predominantly high-grade pattern tumors exhibited higher proliferation and lower clonal diversity, potentially reflecting large recent subclonal expansions. Co-occurrence of truncal loss of chromosomes 3p and 3q was enriched in predominantly low-/mid-grade tumors, while purely undifferentiated solid-pattern tumors had a higher frequency of truncal arm or focal 3q gains and SMARCA4 gene alterations compared with mixed-pattern tumors with a solid component, suggesting distinct evolutionary trajectories. Clonal evolution analysis revealed that tumors tend to evolve toward higher-grade patterns. The presence of micropapillary pattern and ‘tumor spread through air spaces’ were associated with intrathoracic recurrence, in contrast to the presence of solid/cribriform patterns, necrosis and preoperative circulating tumor DNA detection, which were associated with extra-thoracic recurrence. These data provide insights into the relationship between LUAD morphology, the underlying evolutionary genomic landscape, and clinical and anatomical relapse risk

    The evolution of lung cancer and impact of subclonal selection in TRACERx

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    Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource

    The evolution of non-small cell lung cancer metastases in TRACERx

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    Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse
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