An improved method of computing geometrical potential force (GPF) employed in the segmentation of 3D and 4D medical images

The geometric potential force (GPF) used in segmentation of medical images is in general a robustmethod. However, calculation of the GPF is often time consuming and slow. In the present work, wepropose several methods for improving the GPF calculation and evaluate their efficiency against theoriginal method. Among different methods investigated, the procedure that combines Riesz transformand integration by part provides the fastest solution. Both static and dynamic images have been employedto demonstrate the efficacy of the proposed methods

Local is not always better: the impact of climate information on values, behavior and policy support

In the current research, we experimentally examined the effect of providing local or global information about the impacts of climate change on individuals’ perceived importance of climate change and on their willingness to take action to address it, including policy support. We examined these relationships in the context of individuals’ general value orientations. Our findings, from 99 US residents, suggest that different kinds of climate information (local, global, or none) interact with values vis-à-vis our dependent variables. Specifically, while self-transcendent values predict perceived importance and pro-environmental behavior across all three information conditions, the effect on policy support is less clear. Furthermore, we detected a “reactance effect” where individuals with self-enhancing values who read local information thought that climate change was less important and were less willing to engage in pro-environmental behavior and support policy than self-enhancing individuals in the other information conditions. These results suggest that policy makers and public communicators may want to be cognizant of their audience’s general value orientation. Local information may not only be ineffective but may also prove counterproductive with individuals whose value orientations are more self-enhancing than self-transcendent

Quantification of key retinal features in early and late age-related macular degeneration using deep learning

PURPOSE: To develop and validate a deep learning model for segmentation of 13 features associated with neovascular and atrophic age-related macular degeneration (AMD). DESIGN: Development and validation of a deep-learning model for feature segmentation METHODS: Data for model development were obtained from 307 optical coherence tomography volumes. Eight experienced graders manually delineated all abnormalities in 2,712 B-scans. A deep neural network was trained with this data to perform voxel-level segmentation of the 13 most common abnormalities (features). For evaluation, 112 B-scans from 112 patients with a diagnosis of neovascular AMD were annotated by four independent observers. Main outcome measures were Dice score, intra-class correlation coefficient (ICC), and free-response receiver operating characteristic (FROC) curve. RESULTS: On 11 of the 13 features, the model obtained a mean Dice score of 0.63 ± 0.15, compared to 0.61 ± 0.17 for the observers. The mean ICC for the model was 0.66 ± 0.22, compared to 0.62 ± 0.21 for the observers. Two features were not evaluated quantitatively due to lack of data. FROC analysis demonstrated that the model scored similar or higher sensitivity per false positives compared to the observers. CONCLUSIONS: The quality of the automatic segmentation matches that of experienced graders for most features, exceeding human performance for some features. The quantified parameters provided by the model can be used in the current clinical routine and open possibilities for further research into treatment response outside clinical trials

Intracellular Spatial Localization Regulated by the Microtubule Network

The commonly recognized mechanisms for spatial regulation inside the cell are membrane-bounded compartmentalization and biochemical association with subcellular organelles. We use computational modeling to investigate another spatial regulation mechanism mediated by the microtubule network in the cell. Our results demonstrate that the mitotic spindle can impose strong sequestration and concentration effects on molecules with binding affinity for microtubules, especially dynein-directed cargoes. The model can recapitulate the essence of three experimental observations on distinct microtubule network morphologies: the sequestration of germ plasm components by the mitotic spindles in the Drosophila syncytial embryo, the asymmetric cell division initiated by the time delay in centrosome maturation in the Drosophila neuroblast, and the diffusional block between neighboring energids in the Drosophila syncytial embryo. Our model thus suggests that the cell cycle-dependent changes in the microtubule network are critical for achieving different spatial regulation effects. The microtubule network provides a spatially extensive docking platform for molecules and gives rise to a “structured cytoplasm”, in contrast to a free and fluid environment

Immunological assays for chemokine detection in in-vitro culture of CNS cells

Herein we review the various methods currently in use for determining the expression of chemokines by CNS cells in vitro. Chemokine detection assays are used in conjuction with one another to provide a comprehensive, biologically relevant assessment of the chemokines which is necessary for correct data interpretation of a specific observed biological effect. The methods described include bioassays for soluble chemokine receptors, RNA extraction, RT-PCR, Real - time quantitative PCR, gene array analysis, northern blot analysis, Ribonuclease Protection assay, Flow cytometry, ELISPOT, western blot analysis, and ELISA. No single method of analysis meets the criteria for a comprehensive, biologically relevant assessment of the chemokines, therefore more than one assay might be necessary for correct data interpretation, a choice that is based on development of a scientific rationale for the method with emphasis on the reliability and relevance of the method

Clinical features and pitfalls in the laboratory diagnosis of dengue in travellers

BACKGROUND: Several enzyme-linked immunosorbent assay (ELISA)-kits are commercially available for the rapid diagnosis of dengue infection, and have demonstrated good sensitivity and specificity in paired serum samples. In practice, however, often only one blood sample is available from febrile travellers returning from dengue endemic areas. METHODS: To evaluate the diagnostic value of positive dengue antibody-titres performed by a standard ELISA (PanBio IgM- and IgG-ELISA) in single serum samples (regarded as "probable infection"), 127 positive samples were further analyzed using envelope/membrane IgM-, and nonstructural protein 1 IgM- and IgG-ELISAs, immunofluorescence assays, and real-time reverse transcription polymerase chain reaction assays (RT-PCR). A combination of the test-results served as the diagnostic "gold standard". A total of 1,035 febrile travellers returning from dengue-endemic countries with negative dengue-serology and RT-PCR served as controls to compare clinical and haematological features. RESULTS: Overall, only 64 (positive predictive value = 50%) of the probable cases were confirmed by additional analysis and 54 (42.5%) were confirmed to be "false-positive". Rash was the only clinical feature significantly associated with confirmed dengue fever. The combination of thrombocytopenia and leucopenia was present in 40.4% of confirmed and in 6.1% of false-positive cases. Thus, the positive predictive value for the combination of positive PanBio-ELISA plus the two haematological features was 90.5%. CONCLUSION: The examination of paired serum samples is considered the most reliable serodiagnostic procedure for dengue. However, if only one blood sample is available, a single positive ELISA-result carries a high rate of false-positivity and should be confirmed using a second and more specific diagnostic technique. In the absence of further testing, platelet and white blood cell counts are helpful for the correct interpretation

Differentiation of human multipotent dermal fibroblasts into islet-like cell clusters

<p>Abstract</p> <p>Background</p> <p>We have previously obtained a clonal population of cells from human foreskin that is able to differentiate into mesodermal, ectodermal and endodermal progenies. It is of great interest to know whether these cells could be further differentiated into functional insulin-producing cells.</p> <p>Results</p> <p>Sixty-one single-cell-derived dermal fibroblast clones were established from human foreskin by limiting dilution culture. Of these, two clones could be differentiated into neuron-, adipocyte- or hepatocyte-like cells under certain culture conditions. In addition, those two clones were able to differentiate into islet-like clusters under pancreatic induction. Insulin, glucagon and somatostatin were detectable at the mRNA and protein levels after induction. Moreover, the islet-like clusters could release insulin in response to glucose in vitro.</p> <p>Conclusions</p> <p>This is the first study to demonstrate that dermal fibroblasts can differentiate into insulin-producing cells without genetic manipulation. This may offer a safer cell source for future stem cell-based therapies.</p