Increase in perceived case suspiciousness due to local contrast optimisation in digital screening mammography

Item does not contain fulltextOBJECTIVES: To determine the influence of local contrast optimisation on diagnostic accuracy and perceived suspiciousness of digital screening mammograms. METHODS: Data were collected from a screening region in the Netherlands and consisted of 263 digital screening cases (153 recalled,110 normal). Each case was available twice, once processed with a tissue equalisation (TE) algorithm and once with local contrast optimisation (PV). All cases had digitised previous mammograms. For both algorithms, the probability of malignancy of each finding was scored independently by six screening radiologists. Perceived case suspiciousness was defined as the highest probability of malignancy of all findings of a radiologist within a case. Differences in diagnostic accuracy of the processing algorithms were analysed by comparing the areas under the receiver operating characteristic curves (A(z)). Differences in perceived case suspiciousness were analysed using sign tests. RESULTS: There was no significant difference in A(z) (TE: 0.909, PV 0.917, P = 0.46). For all radiologists, perceived case suspiciousness using PV was higher than using TE more often than vice versa (ratio: 1.14-2.12). This was significant (P <0.0083) for four radiologists. CONCLUSIONS: Optimisation of local contrast by image processing may increase perceived case suspiciousness, while diagnostic accuracy may remain similar. KEY POINTS: Variations among different image processing algorithms for digital screening mammography are large. Current algorithms still aim for optimal local contrast with a low dynamic range. Although optimisation of contrast may increase sensitivity, diagnostic accuracy is probably unchanged. Increased local contrast may render both normal and abnormal structures more conspicuous.1 april 201

Gene Expression Profiling of Preovulatory Follicle in the Buffalo Cow: Effects of Increased IGF-I Concentration on Periovulatory Events

The preovulatory follicle in response to gonadotropin surge undergoes dramatic biochemical, and morphological changes orchestrated by expression changes in hundreds of genes. Employing well characterized bovine preovulatory follicle model, granulosa cells (GCs) and follicle wall were collected from the preovulatory follicle before, 1, 10 and 22 h post peak LH surge. Microarray analysis performed on GCs revealed that 450 and 111 genes were differentially expressed at 1 and 22 h post peak LH surge, respectively. For validation, qPCR and immunocytochemistry analyses were carried out for some of the differentially expressed genes. Expression analysis of many of these genes showed distinct expression patterns in GCs and the follicle wall. To study molecular functions and genetic networks, microarray data was analyzed using Ingenuity Pathway Analysis which revealed majority of the differentially expressed genes to cluster within processes like steroidogenesis, cell survival and cell differentiation. In the ovarian follicle, IGF-I is established to be an important regulator of the above mentioned molecular functions. Thus, further experiments were conducted to verify the effects of increased intrafollicular IGF-I levels on the expression of genes associated with the above mentioned processes. For this purpose, buffalo cows were administered with exogenous bGH to transiently increase circulating and intrafollicular concentrations of IGF-I. The results indicated that increased intrafollicular concentrations of IGF-I caused changes in expression of genes associated with steroidogenesis (StAR, SRF) and apoptosis (BCL-2, FKHR, PAWR). These results taken together suggest that onset of gonadotropin surge triggers activation of various biological pathways and that the effects of growth factors and peptides on gonadotropin actions could be examined during preovulatory follicle development

High Arctic wetting reduces permafrost carbon feedbacks to climate warming

The carbon (C) balance of permafrost regions is predicted to be extremely sensitive to climatic changes. Major uncertainties exist in the rate of permafrost thaw and associated C emissions (33–508 Pg C or 0.04–1.69 °C by 2100) and plant C uptake. In the High Arctic, semi-deserts retain unique soil–plant–permafrost interactions and heterogeneous soil C pools (>12 Pg C). Owing to its coastal proximity, marked changes are expected for High Arctic tundra. With declining summer sea-ice cover, these systems are simultaneously exposed to rising temperatures, increases in precipitation and permafrost degradation. Here we show, using measurements of tundra–atmosphere C fluxes and soil C sources (C) at a long-term climate change experiment in northwest Greenland, that warming decreased the summer CO2 sink strength of semi-deserts by up to 55%. In contrast, warming combined with wetting increased the CO2 sink strength by an order of magnitude. Further, wetting while relocating recently assimilated plant C into the deep soil decreased old C loss compared with the warming-only treatment. Consequently, the High Arctic has the potential to remain a strong C sink even as the rest of the permafrost region transitions to a net C source as a result of future global warming

Permafrost-carbon complexities

The thawing and decomposition of carbon stored in permafrost generates greenhouse gases that could further intensify global warming. Currently, most of the thawed carbon is assumed to be converted to greenhouse gases, such as carbon dioxide and methane, and carbon decomposition is thought to only occur at the site of the thaw. We argue that lateral transport of thawed permafrost carbon from land to ocean will translocate greenhouse gas release away from the thaw site, and that storage and burial of thawed carbon in long- and short-term reservoirs will attenuate greenhouse gas emissions

Regional Climate Change Policy Under Positive Feedbacks and Strategic Interactions

The surface albedo feedback, along with heat and moisture transport from the Equator to the Poles, is associated with polar amplification which is a well-established scientific fact. The present paper extends (Brock and Xepapadeas in Eur Econ Rev 94:263–282, 2017) to a non-cooperative framework with polar amplification, where regions decide emissions by maximizing own welfare. This can be regarded as a case of regional non-cooperation regarding climate change. Open loop and feedback solutions are derived and compared, in terms of temperature paths and welfare, with the cooperative solution. Carbon taxes which could bridge the gap between cooperative and non-cooperative emissions path are also derived. Finally, the framework is extended to a Ramsey set-up in which it is shown how the regional climate model can be coupled with standard optimal growth models. Numerical simulations confirm the theoretical results and provide insights about the size and the direction of deviations between the cooperative and the non-cooperative solutions