Comprehensive two-dimensional gas chromatography (GC x GC) measurements of volatile organic compounds in the atmosphere

Abstract. During the MINOS campaign in August 2001 comprehensive two-dimensional gas chromatography (GC×GC) was applied to the in situ measurements of atmospheric volatile organic compounds (VOCs) at the Finokalia ground station, Crete. The measurement system employs a thermal desorption unit for on-line sampling and injection, and a GC×GC separation system equipped with a flame ionization detector (FID) for detection. The system was optimized to resolve C7 − C14 organic components. Two-dimensional chromatograms from measurements of Finokalia air samples show several hundred wellseparated peaks. To facilitate peak identification, cartridge samples collected at Finokalia were analyzed using the same GC×GC system coupled with a time-of-flight mass spectrometer (TOF-MS). The resulting mass spectra were deconvoluted and compared to spectra from a database for tentative peak identification. About 650 peaks have been identified in the two-dimensional plane, with significant signal/noise ratios (>100) and high spectra similarities (>800). By comparing observed retention indices with those found in the literature, 235 of the identifications have been confirmed. 150 of the confirmed compounds show up in the C7 − C14 range of the chromatogram from the in situ measurement. However, at least as many peaks remain unidentified. For quantification of the GC×GC measurements, peak volumes of measured compounds have been integrated and externally calibrated using a standard gas mixture.

Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images

Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer that can progress into invasive ductal carcinoma (IDC). Studies suggest DCIS is often overtreated since a considerable part of DCIS lesions may never progress into IDC. Lower grade lesions have a lower progression speed and risk, possibly allowing treatment de-escalation. However, studies show significant inter-observer variation in DCIS grading. Automated image analysis may provide an objective solution to address high subjectivity of DCIS grading by pathologists. In this study, we developed a deep learning-based DCIS grading system. It was developed using the consensus DCIS grade of three expert observers on a dataset of 1186 DCIS lesions from 59 patients. The inter-observer agreement, measured by quadratic weighted Cohen's kappa, was used to evaluate the system and compare its performance to that of expert observers. We present an analysis of the lesion-level and patient-level inter-observer agreement on an independent test set of 1001 lesions from 50 patients. The deep learning system (dl) achieved on average slightly higher inter-observer agreement to the observers (o1, o2 and o3) ($\kappa_{o1,dl}=0.81, \kappa_{o2,dl}=0.53, \kappa_{o3,dl}=0.40$) than the observers amongst each other ($\kappa_{o1,o2}=0.58, \kappa_{o1,o3}=0.50, \kappa_{o2,o3}=0.42$) at the lesion-level. At the patient-level, the deep learning system achieved similar agreement to the observers ($\kappa_{o1,dl}=0.77, \kappa_{o2,dl}=0.75, \kappa_{o3,dl}=0.70$) as the observers amongst each other ($\kappa_{o1,o2}=0.77, \kappa_{o1,o3}=0.75, \kappa_{o2,o3}=0.72$). In conclusion, we developed a deep learning-based DCIS grading system that achieved a performance similar to expert observers. We believe this is the first automated system that could assist pathologists by providing robust and reproducible second opinions on DCIS grade

External validation and clinical utility assessment of PREDICT breast cancer prognostic model in young, systemic treatment-naïve women with node-negative breast cancer

Background: The validity of the PREDICT breast cancer prognostic model is unclear for young patients without adjuvant systemic treatment. This study aimed to validate PREDICT and assess its clinical utility in young women with node-negative breast cancer who did not receive systemic treatment. Methods: We selected all women from the Netherlands Cancer Registry who were diagnosed with node-negative breast cancer under age 40 between 1989 and 2000, a period when adjuvant systemic treatment was not standard practice for women with node-negative disease. We evaluated the calibration and discrimination of PREDICT using the observed/expected (O/E) mortality ratio, and the area under the receiver operating characteristic curve (AUC), respectively. Additionally, we compared the potential clinical utility of PREDICT for selectively administering chemotherapy to the chemotherapy-to-all strategy using decision curve analysis at predefined thresholds. Results: A total of 2264 women with a median age at diagnosis of 36 years were included. Of them, 71.2% had estrogen receptor (ER)-positive tumors and 44.0% had grade 3 tumors. Median tumor size was 16 mm. PREDICT v2.2 underestimated 10-year all-cause mortality by 33% in all women (O/E ratio:1.33, 95%CI:1.22–1.43). Model discrimination was moderate overall (AUC10-year:0.65, 95%CI:0.62–0.68), and poor for women with ER-negative tumors (AUC10-year:0.56, 95%CI:0.51–0.62). Compared to the chemotherapy-to-all strategy, PREDICT only showed a slightly higher net benefit in women with ER-positive tumors, but not in women with ER-negative tumors. Conclusions: PREDICT yields unreliable predictions for young women with node-negative breast cancer. Further model updates are needed before PREDICT can be routinely used in this patient subset.</p

Glutathione S-transferase M1-null genotype as risk factor for SOS in oxaliplatin-treated patients with metastatic colorectal cancer

Background: Oxaliplatin is used as a neo-adjuvant therapy in hepatic colorectal carcinoma metastasis. This treatment has significant side effects, as oxaliplatin is toxic to the sinusoidal endothelial cells and can induce sinusoidal obstruction syndrome (SOS), which is related to decreased overall survival. Glutathione has an important role in the defence system, catalysed by glutathione S-transferase (GST), including two non-enzyme producing polymorphisms (GSTM1-null and GSTT1-null). We hypothesise that patients with a non-enzyme producing polymorphism have a higher risk of developing toxic injury owing to oxaliplatin. Methods: In the nontumour-bearing liver, the presence of SOS was studied histopathologically. The genotype was determined by a semi-nested PCR. Results: Thirty-two of the 55 (58%) patients showed SOS lesions, consisting of 27% mild, 22% moderate and 9% severe lesions. The GSTM1-null genotype was present in 25 of the 55 (46%). Multivariate analysis showed that the GSTM1-null genotype significantly correlated with the presence of (moderate-severe) SOS (P=0.026). Conclusion: The GSTM1-null genotype is an independent risk factor for SOS. This finding allows us, in association with other risk factors, to conceive a potential risk profile predicting whether the patient is at risk of developing SOS, before starting oxaliplatin, and subsequently might result in adjustment of treatment

Comprehensive two-dimensional gas chromatography (GC × GC) measurements of volatile organic compounds in the atmosphere

International audienceDuring the MINOS campaign in August 2001 comprehensive two-dimensional gas chromatography (GC x GC) was applied to the in situ measurements of atmospheric volatile organic compounds (VOCs) at the Finokalia ground station, Crete. The measurement system employs a thermal desorption unit for on-line sampling and injection, and a GC x GC separation system equipped with a flame ionization detector (FID) for detection. The system was optimized to resolve C7-C14 organic components. Two-dimensional chromatograms from measurements of Finokalia air samples show several hundred well-separated peaks. To facilitate peak identification, cartridge samples collected at Finokalia were analyzed using the same GC x GC system coupled with a time-of-flight mass spectrometer (TOF-MS). The resulting mass spectra were deconvoluted and compared to spectra from a database for tentative peak identification. About 650 peaks have been identified in the two-dimensional plane, with significant signal/noise ratios (>100) and high spectra similarities (>800). By comparing observed retention indices with those found in the literature, 235 of the identifications have been confirmed. 150 of the confirmed compounds show up in the C7-C14 range of the chromatogram from the in situ measurement. However, at least as many peaks remain unidentified. For quantification of the GC x GC measurements, peak volumes of measured compounds have been integrated and externally calibrated using a standard gas mixture