EEG findings of reduced neural synchronization during visual integration in schizophrenia

Schizophrenia patients exhibit well-documented visual processing deficits. One area of disruption is visual integration, the ability to form global objects from local elements. However, most studies of visual integration in schizophrenia have been conducted in the context of an active attention task, which may influence the findings. In this study we examined visual integration using electroencephalography (EEG) in a passive task to elucidate neural mechanisms associated with poor visual integration. Forty-six schizophrenia patients and 30 healthy controls had EEG recorded while passively viewing figures comprised of real, illusory, or no contours. We examined visual P100, N100, and P200 event-related potential (ERP) components, as well as neural synchronization in the gamma (30-60 Hz) band assessed by the EEG phase locking factor (PLF). The N100 was significantly larger to illusory vs. no contour, and illusory vs. real contour stimuli while the P200 was larger only to real vs. illusory stimuli; there were no significant interactions with group. Compared to controls, patients failed to show increased phase locking to illusory versus no contours between 40-60 Hz. Also, controls, but not patients, had larger PLF between 30-40 Hz when viewing real vs. illusory contours. Finally, the positive symptom factor of the BPRS was negatively correlated with PLF values between 40-60 Hz to illusory stimuli, and with PLF between 30-40 Hz to real contour stimuli. These results suggest that the pattern of results across visual processing conditions is similar in patients and controls. However, patients have deficits in neural synchronization in the gamma range during basic processing of illusory contours when attentional demand is limited

Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa

A simple genetic algorithm for calibration of stochastic rock discontinuity networks

Este artículo propone un método para llevar a cabo la calibración de las familias de discontinuidades en macizos rocosos. We present a novel approach for calibration of stochastic discontinuity network parameters based on genetic algorithms (GAs). To validate the approach, examples of application of the method to cases with known parameters of the original Poisson discontinuity network are presented. Parameters of the model are encoded as chromosomes using a binary representation, and such chromosomes evolve as successive generations of a randomly generated initial population, subjected to GA operations of selection, crossover and mutation. Such back-calculated parameters are employed to make assessments about the inference capabilities of the model using different objective functions with different probabilities of crossover and mutation. Results show that the predictive capabilities of GAs significantly depend on the type of objective function considered; and they also show that the calibration capabilities of the genetic algorithm can be acceptable for practical engineering applications, since in most cases they can be expected to provide parameter estimates with relatively small errors for those parameters of the network (such as intensity and mean size of discontinuities) that have the strongest influence on many engineering applications

Spot the Difference-Development of a Syndrome Based Protein Microarray for Specific Serological Detection of Multiple Flavivirus Infections in Travelers

Background The family Flaviviridae, genus Flavivirus, holds many of the world’s most prevalent arboviral diseases that are also considered the most important travel related arboviral infections. In most cases, flavivirus diagnosis in travelers is primarily based on serology as viremia is often low and typically has already been reduced to undetectable levels when symptoms set in and patients seek medical attention. Serological differentiation between flaviviruses and the false-positive results caused by vaccination and cross-reactivity among the different species, are problematic for surveillance and diagnostics of flaviviruses. Their partially overlapping geographic distribution and symptoms, combined with increase in travel, and preexisting antibodies due to flavivirus vaccinations, expand the need for rapid and reliable multiplex diagnostic tests to supplement currently used methods. Goal We describe the development of a multiplex serological protein microarray using recombinant NS1 proteins for detection of medically important viruses within the genus Flavivirus. Sera from clinical flavivirus patients were used for primary development of the protein microarray. Results Results show a high IgG and IgM sensitivity and specificity for individual NS1 antigens, and limited cross reactivity, even within serocomplexes. In addition, the serology based on this array allows for discrimination between infection and vaccination response for JEV vaccine, and no cross-reactivity with TBEV and YFV vaccine induced antibodies when testing for antibodies to other flaviviruses. Conclusion Based on these data, multiplex NS1-based protein microarray is a promising tool for surveillance and diagnosis of flaviviruses.

Two serological approaches for detection of antibodies to SARS-CoV-2 in different scenarios: a screening tool and a point-of-care test

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected more than 8 million people worldwide, becoming a pandemic. Detecting antibodies against SARS-CoV-2 is of utmost importance and a good indicator of exposure and circulation of the virus within the general population. Two serological tools based on a double recognition assay [enzyme-linked immunosorbent assay (DR-ELISA) and lateral flow assay (DR-LFA)] to detect total antibodies to SARS-CoV-2 have been developed based on the recombinant nucleocapsid protein. A total of 1065 serum samples, including positive for COVID-19 and negative samples from healthy donors or infected with other respiratory pathogens, were analyzed. The results showed values of sensitivity between 91.2% and 100%, and specificity of 100% and 98.2% for DR-LFA and DR-ELISA, respectively. No cross-reactivity against seasonal coronavirus (HCoV-NL63, HCoV-229E, HCoV-HKU1, HCoV-OC43) was found. These results demonstrate the importance of serology as a complementary tool to polymerase chain reaction for follow-up of recovered patients and identification of asymptomatic individuals

Influence of drying process and particle size of persimmon fibre on its physicochemical, antioxidant, hydration and emulsifying properties

[EN] Persimmon, given its current surplus production, could be an alternative source for the extraction of certain interesting ingredients for the food industry and human health, such as fibre. Thus, the aim of this study was to analyse the influence of hot air and freeze-drying, as well as the particle size of fibre extracted from persimmon peels or pulp on their physicochemical, antioxidant, hydration and emulsifying properties, compared to commercial fibres (from peach, lemon, orange and apple). The results showed that both freeze-dried persimmon pulp and freeze-dried peel had better hydration properties and oil holding capacity than other fibres analysed, although the swelling capacity was higher for lemon fibre. Freeze-dried persimmon peel fibre showed higher values of emulsion stability than commercial fibres. 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Accelerated expansion from ghost-free bigravity: a statistical analysis with improved generality

We study the background cosmology of the ghost-free, bimetric theory of gravity. We perform an extensive statistical analysis of the model using both frequentist and Bayesian frameworks and employ the constraints on the expansion history of the Universe from the observations of supernovae, the cosmic microwave background and the large scale structure to estimate the model's parameters and test the goodness of the fits. We explore the parameter space of the model with nested sampling to find the best-fit chi-square, obtain the Bayesian evidence, and compute the marginalized posteriors and mean likelihoods. We mainly focus on a class of sub-models with no explicit cosmological constant (or vacuum energy) term to assess the ability of the theory to dynamically cause a late-time accelerated expansion. The model behaves as standard gravity without a cosmological constant at early times, with an emergent extra contribution to the energy density that converges to a cosmological constant in the far future. The model can in most cases yield very good fits and is in perfect agreement with the data. This is because many points in the parameter space of the model exist that give rise to time-evolution equations that are effectively very similar to those of the $\Lambda$CDM. This similarity makes the model compatible with observations as in the $\Lambda$CDM case, at least at the background level. Even though our results indicate a slightly better fit for the $\Lambda$CDM concordance model in terms of the $p$-value and evidence, none of the models is statistically preferred to the other. However, the parameters of the bigravity model are in general degenerate. A similar but perturbative analysis of the model as well as more data will be required to break the degeneracies and constrain the parameters, in case the model will still be viable compared to the $\Lambda$CDM.Comment: 42 pages, 9 figures; typos corrected in equations (2.12), (2.13), (3.7), (3.8) and (3.9); more discussions added (footnotes 5, 8, 10 and 13) and abstract, sections 4.2, 4.3 and 5 (conclusions) modified in response to referee's comments; references added; acknowledgements modified; all results completely unchanged; matches version accepted for publication in JHE

Sialic Acid Glycobiology Unveils Trypanosoma cruzi Trypomastigote Membrane Physiology.

Trypanosoma cruzi, the flagellate protozoan agent of Chagas disease or American trypanosomiasis, is unable to synthesize sialic acids de novo. Mucins and trans-sialidase (TS) are substrate and enzyme, respectively, of the glycobiological system that scavenges sialic acid from the host in a crucial interplay for T. cruzi life cycle. The acquisition of the sialyl residue allows the parasite to avoid lysis by serum factors and to interact with the host cell. A major drawback to studying the sialylation kinetics and turnover of the trypomastigote glycoconjugates is the difficulty to identify and follow the recently acquired sialyl residues. To tackle this issue, we followed an unnatural sugar approach as bioorthogonal chemical reporters, where the use of azidosialyl residues allowed identifying the acquired sugar. Advanced microscopy techniques, together with biochemical methods, were used to study the trypomastigote membrane from its glycobiological perspective. Main sialyl acceptors were identified as mucins by biochemical procedures and protein markers. Together with determining their shedding and turnover rates, we also report that several membrane proteins, including TS and its substrates, both glycosylphosphatidylinositol-anchored proteins, are separately distributed on parasite surface and contained in different and highly stable membrane microdomains. Notably, labeling for α(1,3)Galactosyl residues only partially colocalize with sialylated mucins, indicating that two species of glycosylated mucins do exist, which are segregated at the parasite surface. Moreover, sialylated mucins were included in lipid-raft-domains, whereas TS molecules are not. The location of the surface-anchored TS resulted too far off as to be capable to sialylate mucins, a role played by the shed TS instead. Phosphatidylinositol-phospholipase-C activity is actually not present in trypomastigotes. Therefore, shedding of TS occurs via microvesicles instead of as a fully soluble form

Agreement between chromogenic in situ hybridisation (CISH) and FISH in the determination of HER2 status in breast cancer

Determination of the HER2/neu (HER2) status in breast carcinoma has become necessary for the selection of breast cancer patients for trastuzumab therapy. Amplification of the gene analysed by fluorescence in situ hybridisation (FISH) or overexpression of the protein determined by immunohistochemistry (IHC) are the two major methods to establish this status. A strong correlation has been previously demonstrated between these two methods. However, FISH is not always feasible in routine practice and weakly positive IHC tumours (2+) do not always correspond to a gene amplification. Our study was performed in order to evaluate the contribution of chromogenic in situ hybridisation (CISH), which enables detection of the gene copies through an immunoperoxidase reaction. CISH was performed in 79 breast carcinomas for which the HER2 status was previously determined by IHC and FISH. The results of IHC, FISH and CISH were compared for each tumour. CISH procedures were successful in 95% of our cases. Whatever the IHC results, we found a very good concordance (96%) between CISH and FISH. Our study confirms that CISH may be an alternative to FISH for the determination of the gene amplification status in 2+ tumours. Our results allow us to think that, in many laboratories, CISH may also be an excellent method to calibrate the IHC procedures or, as a quality control test, to check regularly that the IHC signal is in agreement with the gene statu