Scanning Mechanical Microscopy of Laser Ablated Volumes Related to Inductively Coupled Plasma-Mass Spectrometry

Scanning mechanical microscopy based on the point by point sampling of the target surface was used to characterize volumes of minerals ablated by laser pulses (Nd: YAG, = 1064 nm, 140 μs pulse-width). Differentiated volumes resulting from vaporization and exfoliation mechanisms were selectively measured. Ablated volumes of natural pyrite (cubic FeS2), marcasite (orthorhombic FeS2) and arsenopyrite AsFeS, were transported into an inductively coupled plasma torch for subsequent mass analysis. The log of the S34 Fe57, and As75 mass intensities was linearly correlated with the log of the dimensions of the vaporized crater induced by the laser shots while large particles had no effect on the measured intensities. A memory effect for As was observed when a nylon tube was used to carry the ablated materials into the plasma torch. The memory effect was decreased by using a copper tube resulting probably from a difference in the electrical properties of the tubing systems leading to a lower adsorption of As within the copper tube than for the case of the nylon tube

Gestational breast cancer in New South Wales: A population-based linkage study of incidence, management, and outcomes.

BackgroundThe incidence of gestational breast cancer (GBC) is increasing in high-income countries. Our study aimed to examine the epidemiology, management and outcomes of women with GBC in New South Wales (NSW), Australia.MethodsA retrospective cohort study using linked data from three NSW datasets. The study group comprised women giving birth with a first-time diagnosis of GBC while the comparison group comprised women giving birth without any type of cancer. Outcome measures included incidence of GBC, maternal morbidities, obstetric management, neonatal mortality, and preterm birth.ResultsBetween 1994 and 2013, 122 women with GBC gave birth in NSW (crude incidence 6.8/ 100,000, 95%CI: 5.6-8.0). Women aged ≥35 years had higher odds of GBC (adjusted odds ratio (AOR) 6.09, 95%CI 4.02-9.2) than younger women. Women with GBC were more likely to give birth by labour induction or pre-labour CS compared to women with no cancer (AOR 4.8, 95%CI: 2.96-7.79). Among women who gave birth by labour induction or pre-labour CS, the preterm birth rate was higher for women with GBC than for women with no cancer (52% vs 7%; AOR 17.5, 95%CI: 11.3-27.3). However, among women with GBC, preterm birth rate did not differ significantly by timing of diagnosis or cancer stage. Babies born to women with GBC were more likely to be preterm (AOR 12.93, 95%CI 8.97-18.64), low birthweight (AOR 8.88, 95%CI 5.87-13.43) or admitted to higher care (AOR 3.99, 95%CI 2.76-5.76) than babies born to women with no cancer.ConclusionWomen aged ≥35 years are at increased risk of GBC. There is a high rate of preterm birth among women with GBC, which is not associated with timing of diagnosis or cancer stage. Most births followed induction of labour or pre-labour CS, with no major short term neonatal morbidity

Most Lung and Colon Cancer Susceptibility Genes Are Pair-Wise Linked in Mice, Humans and Rats

Genetic predisposition controlled by susceptibility quantitative trait loci (QTLs) contributes to a large proportion of common cancers. Studies of genetics of cancer susceptibility, however, did not address systematically the relationship between susceptibility to cancers in different organs. We present five sets of data on genetic architecture of colon and lung cancer susceptibility in mice, humans and rats. They collectively show that the majority of genes for colon and lung cancer susceptibility are linked pair-wise and are likely identical or related. Four CcS/Dem recombinant congenic strains, each differing from strain BALB/cHeA by a different small random subset of ±12.5% of genes received from strain STS/A, suggestively show either extreme susceptibility or extreme resistance for both colon and lung tumors, which is unlikely if the two tumors were controlled by independent susceptibility genes. Indeed, susceptibility to lung cancer (Sluc) loci underlying the extreme susceptibility or resistance of such CcS/Dem strains, mapped in 226 (CcS-10×CcS-19)F2 mice, co-localize with susceptibility to colon cancer (Scc) loci. Analysis of additional Sluc loci that were mapped in OcB/Dem strains and Scc loci in CcS/Dem strains, respectively, shows their widespread pair-wise co-localization (P = 0.0036). Finally, the majority of published human and rat colon cancer susceptibility genes map to chromosomal regions homologous to mouse Sluc loci. 12/12 mouse Scc loci, 9/11 human and 5/7 rat colon cancer susceptibility loci are close to a Sluc locus or its homologous site, forming 21 clusters of lung and colon cancer susceptibility genes from one, two or three species. Our data shows that cancer susceptibility QTLs can have much broader biological effects than presently appreciated. It also demonstrates the power of mouse genetics to predict human susceptibility genes. Comparison of molecular mechanisms of susceptibility genes that are organ-specific and those with trans-organ effects can provide a new dimension in understanding individual cancer susceptibility

X-ray multilayer monochromator with enhanced performance

International audienceAn x-ray multilayer monochromator with improved resolution and a low specular background is presented. The monochromator consists of a lamellar multilayer amplitude grating with appropriate parameters used at the zeroth diffraction order. The device is fabricated by means of combining deposition of thin films on a nanometer scale, UV lithography, and reactive ion etching. The performance of this new monochromator at photon energies near 1500 eV is shown

Prognostic value of microvessel density in stage II and III colon cancer patients:a retrospective cohort study

Background Microvessel density (MVD), as a derived marker for angiogenesis, has been associated with poor outcome in several types of cancer. This study aimed to evaluate the prognostic value of MVD in stage II and III colon cancer and its relation to tumour-stroma-percentage (TSP) and expression of HIF1A and VEGFA. Methods Formalin-fixed paraffin-embedded (FFPE) colon cancer tissues were collected from 53 stage II and 54 (5-fluorouracil-treated) stage III patients. MVD was scored by digital morphometric analysis of CD31-stained whole tumour sections. TSP was scored using haematoxylin-eosin stained slides. Protein expression of HIF1A and VEGFA was determined by immunohistochemical evaluation of tissue microarrays. Results Median MVD was higher in stage III compared to stage II colon cancers (11.1% versus 5.6% CD31-positive tissue area, p <0.001). High MVD in stage II patients tended to be associated with poor disease free survival (DFS) in univariate analysis (p = 0.056). In contrast, high MVD in 5FU-treated stage III patients was associated with better DFS (p = 0.006). Prognostic value for MVD was observed in multivariate analyses for both cancer stages. Conclusions MVD is an independent prognostic factor associated with poor DFS in stage II colon cancer patients, and with better DFS in stage III colon cancer patients treated with adjuvant chemotherapy

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Aim To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.Financial support for this study was provided by a grant from ZonMw (Grant number: 848015007). ZonMw had no role in designing the study, interpreting the data, writing the manuscript, and publishing the report

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Aim: To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods: A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results: Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion: This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies