49 resultados para Foliar diagnosis
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Aim: A nested case-control discovery study was undertaken 10 test whether information within the serum peptidome can improve on the utility of CA125 for early ovarian cancer detection. Materials and Methods: High-throughput matrix-assisted laser desorption ionisation mass spectrometry (MALDI-MS) was used to profile 295 serum samples from women pre-dating their ovarian cancer diagnosis and from 585 matched control samples. Classification rules incorporating CA125 and MS peak intensities were tested for discriminating ability. Results: Two peaks were found which in combination with CA125 discriminated cases from controls up to 15 and 11 months before diagnosis, respectively, and earlier than using CA125 alone. One peak was identified as connective tissue-activating peptide III (CTAPIII), whilst the other was putatively identified as platelet factor 4 (PF4). ELISA data supported the down-regulation of PF4 in early cancer cases. Conclusion: Serum peptide information with CA125 improves lead time for early detection of ovarian cancer. The candidate markers are platelet-derived chemokines, suggesting a link between platelet function and tumour development.
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A chapter outlining a theoretical position on the definition of the speech language disorder, cluttering.
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The effect of increasing salinity on a range of chlorophyll fluorescence parameters in foliar tissue of 30 Acer genotypes was examined. The magnitude of the fluorescence responses differed among genotypes ranging from minor effects to substantial leaf tissue damage. Interpretation of the fluorescence expressions provided an insight into mechanisms of salt damage and resilience among genotypes. Based on reductions in a performance index (PIp) following salinity, genotypes were ranked in order from tolerant to sensitive. Based on this ranking criterion, marked differences in salt tolerance among genotypes were distinguished. It is concluded that chlorophyll fluorescence offers a rapid screening technique for assessing the foliar salinity tolerance of urban trees.
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The time-mean quasi-geostrophic potential vorticity equation of the atmospheric flow on isobaric surfaces can explicitly include an atmospheric (internal) forcing term of the stationary-eddy flow. In fact, neglecting some non-linear terms in this equation, this forcing can be mathematically expressed as a single function, called Empirical Forcing Function (EFF), which is equal to the material derivative of the time-mean potential vorticity. Furthermore, the EFF can be decomposed as a sum of seven components, each one representing a forcing mechanism of different nature. These mechanisms include diabatic components associated with the radiative forcing, latent heat release and frictional dissipation, and components related to transient eddy transports of heat and momentum. All these factors quantify the role of the transient eddies in forcing the atmospheric circulation. In order to assess the relevance of the EFF in diagnosing large-scale anomalies in the atmospheric circulation, the relationship between the EFF and the occurrence of strong North Atlantic ridges over the Eastern North Atlantic is analyzed, which are often precursors of severe droughts over Western Iberia. For such events, the EFF pattern depicts a clear dipolar structure over the North Atlantic; cyclonic (anticyclonic) forcing of potential vorticity is found upstream (downstream) of the anomalously strong ridges. Results also show that the most significant components are related to the diabatic processes. Lastly, these results highlight the relevance of the EFF in diagnosing large-scale anomalies, also providing some insight into their interaction with different physical mechanisms.
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Using a discrete wavelet transform with a Meyer wavelet basis, we present a new quantitative algorithm for determining the onset time of Pi1 and Pi2 ULF waves in the nightside ionosphere with ∼20- to 40-s resolution at substorm expansion phase onset. We validate the algorithm by comparing both the ULF wave onset time and location to the optical onset determined by the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE)–Far Ultraviolet Imager (FUV) instrument. In each of the six events analyzed, five substorm onsets and one pseudobreakup, the ULF onset is observed prior to the global optical onset observed by IMAGE at a station closely conjugate to the optical onset. The observed ULF onset times expand both latitudinally and longitudinally away from an epicenter of ULF wave power in the ionosphere. We further discuss the utility of the algorithm for diagnosing pseudobreakups and the relationship of the ULF onset epicenter to the meridians of elements of the substorm current wedge. The importance of the technique for establishing the causal sequence of events at substorm onset, especially in support of the multisatellite Time History of Events and Macroscale Interactions During Substorms (THEMIS) mission, is also described.
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Worldwide, many people are zinc (Zn)-deficient. Dietary Zn intake can be increased by producing crops with higher concentrations of Zn in their edible portions. This can be achieved by applying Zn-fertilisers to varieties with an increased ability to acquire Zn and to accumulate Zn in their edible portions. Potato (Solanum tuberosum L.) is an important food crop and is, therefore, a target for bio-fortification with Zn. Field trials incorporating a core collection of 23 potato genotypes, performed over 4 years (2006 – 2009), indicated significant genotypic effects on tuber Zn concentration and suggested that tuber Zn concentration was influenced by environmental effects, but also found that genotype environment (G E) interactions were not significant. Tuber Zn concentrations averaged 10.8 mg kg–1 dry matter (DM), and the ratio between the lowest and the highest varietal tuber Zn-concentration averaged 1.76. Tuber Zn concentrations could be increased by foliar Zn-fertilisation. Tuber yields of ‘Maris Piper’ were unaffected by foliar applications of < 1.08 g Zn plant–1. The relationship between tuber Zn concentration and foliar Zn application followed a saturation curve, reaching a maximum at approx. 30 mg Zn kg–1 DM at a foliar Zn application rate of 1.08 g plant–1. Despite a 40-fold increase in shoot Zn concentration compared to the unfertilised controls following foliar Zn fertilisation with 2.16 g Zn plant–1, only a doubling in tuber Zn concentration was observed. This suggests that the biofortification of tubers with Zn was restricted by the limited mobility of Zn in the phloem. A significant positive linear relationship between tuber Zn concentration and tuber N concentration supported the hypothesis of co-transport of Zn and N-compounds in the phloem.
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Doctor-patient jokes are universally popular because of the information asymmetries within the diagnostic relationship. We contend that entrepreneurial diagnosis is present in markets where consumers are unable to diagnose their own problems and, instead, may rely on the entrepreneur to diagnose them. Entrepreneurial diagnosis is a cognitive skill possessed by the entrepreneur. It is an identifiable subset of entrepreneurial judgment and can be modeled – which we attempt to do. In order to overcome the information asymmetries and exploit opportunities, we suggest that entrepreneurs must invest in market making innovations (as distinct from product innovations) such as trustworthy reputations. The diagnostic entrepreneur described in this paper represents a creative response to difficult diagnostic problems and helps to explain the success of many firms whose products are not particularly innovative but which are perceived as offering high standards of service. These firms are trusted not only for their truthfulness about the quality of their product, but for their honesty, confidentiality and understanding in helping customers identify the most appropriate product to their needs.
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We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.
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Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.
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Immunodiagnostic microneedles provide a novel way to extract protein biomarkers from the skin in a minimally invasive manner for analysis in vitro. The technology could overcome challenges in biomarker analysis specifically in solid tissue, which currently often involves invasive biopsies. This study describes the development of a multiplex immunodiagnostic device incorporating mechanisms to detect multiple antigens simultaneously, as well as internal assay controls for result validation. A novel detection method is also proposed. It enables signal detection specifically at microneedle tips and therefore may aid the construction of depth profiles of skin biomarkers. The detection method can be coupled with computerised densitometry for signal quantitation. The antigen specificity, sensitivity and functional stability of the device were assessed against a number of model biomarkers. Detection and analysis of endogenous antigens (interleukins 1α and 6) from the skin using the device was demonstrated. The results were verified using conventional enzyme-linked immunosorbent assays. The detection limit of the microneedle device, at ≤10 pg/mL, was at least comparable to conventional plate-based solid-phase enzyme immunoassays.
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This chapter reconsiders critiques of pre-natal diagnosis in Disability Studies. Underlying assumptions about reproductive technologies are analysed to demonstrate that while many critiques of pre-natal diagnosis by Disability activists and theorists are concerned about children being the product of 'choice' through the selective effects of pre-natal diagnosis, the issue that reproductive technologies (such as IVF) themselves necessarily always already rely on 'choice' -- namely the choice for a 'biological' or 'own' child (different terms are used) -- is nowhere considered. The chapter considers several consequences of thinking through this issue and its implications.
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Background Depression and anxiety are common after diagnosis of breast cancer. We examined to what extent these are recurrences of previous disorder and, controlling for this, whether shame, self-blame and low social support after diagnosis predicted onset of depression and anxiety subsequently. Method Women with primary breast cancer who had been treated surgically self-reported shame, self-blame, social support and emotional distress post-operatively. Psychiatric interview 12 months later identified those with adult lifetime episodes of major depression (MD) or generalized anxiety disorder (GAD) before diagnosis and onset over the subsequent year. Statistical analysis examined predictors of each disorder in that year. Results Of the patients, two-thirds with episodes of MD and 40% with episodes of GAD during the year after diagnosis were experiencing recurrence of previous disorder. Although low social support, self-blame and shame were each associated with both MD and GAD after diagnosis, they did not mediate the relationship of disorder after diagnosis with previous disorder. Low social support, but not shame or self-blame, predicted recurrence after controlling for previous disorder. Conclusions Anxiety and depression during the first year after diagnosis of breast cancer are often the recurrence of previous disorder. In predicting disorder following diagnosis, self-blame and shame are merely markers of previous disorder. Low social support is an independent predictor and therefore may have a causal role.
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INTRODUCTION Due to their specialist training, breast care nurses (BCNs) should be able to detect emotional distress and offer support to breast cancer patients. However, patients who are most distressed after diagnosis generally experience least support from care staff. To test whether BCNs overcome this potential barrier, we compared the support experienced by depressed and non-depressed patients from their BCNs and the other main professionals involved in their care: surgeons and ward nurses. PATIENTS AND METHODS Women with primary breast cancer (n = 355) 2–4 days after mastectomy or wide local excision, self-reported perceived professional support and current depression. Analysis of variance compared support ratings of depressed and non-depressed patients across staff types. RESULTS There was evidence of depression in 31 (9%) patients. Depressed patients recorded less surgeon and ward nurse support than those who were not depressed but the support received by patients from the BCN was high, whether or not patients were depressed. CONCLUSIONS BCNs were able to provide as much support to depressed patients as to non-depressed patients, whereas depressed patients felt less supported by surgeons and ward nurses than did non-depressed patients. Future research should examine the basis of BCNs' ability to overcome barriers to support in depressed patients. Our findings confirm the importance of maintaining the special role of the BCN.