46 resultados para diluizione,olio,CFD,MCI


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In 1875, 7 years prior to the description of the Koch bacillus, Klebs visualized the first Streptococcus pneumoniae in a pleural fluid. Since then, this organism has played a determinant role in biomedical science. From a biological point of view, it was largely implicated in the development of passive and active immunization by serotherapy and vaccination, respectively. Genetic transformation was also first observed in S. pneumoniae, leading to the discovery of DNA. From a clinical point of view, S. pneumoniae is still today a prime cause of otitis media in children and of pneumonia in all age groups, as well as a predominant cause of meningitis and bacteremia. In adults, bacteremia is still entailed with a mortality of over 25%. Although S. pneumoniae remained very sensitive to penicillin for many years, penicillin-resistance has emerged and increased dramatically over the last 15 years. During this period of time, the frequency of penicillin-resistant isolates has increased from < or = 1% to frequencies varying from 20 to 60% in geographic areas as diverse as South Africa, Spain, France, Hungary, Iceland, Alaska, and numerous regions of the United States and South America. In Switzerland, the current frequency of penicillin-resistant pneumococci ranges between 5 and > or = 10%. The increase in penicillin-resistant pneumococci correlates with the intensive use of beta-lactam antibiotics. The mechanism of resistance is not due to bacterial production of penicillinase, but to an alteration of the bacterial target of penicillin, the so-called penicillin-binding proteins. Resistance is subdivided into (i) inter mediate level resistance (minimal inhibitory concentration [MIC] of penicillin of 0.1-1 mg/L) and (ii) high level resistance (MCI > or = 2 mg/L). The clinical significance of intermediate resistance remains poorly defined. On the other hand, highly resistant strains were responsible for numerous therapeutical failures, especially in cases of meningitis. Antibiotics recommended against penicillin-resistant pneumococci include cefotaxime, ceftriaxone, imipenem and in some instances vancomycin. However, penicillin-resistant pneumococci tend to present cross-resistances to all the antibotics of the beta-lactam family and could even become resistant to the last resort drugs mentioned above. Thus, in conclusion, the explosion of resistance to penicillin in pneumococci is a ubiquitous phenomenon which must be fought against by (i) a strict utilization of antibiotics, (ii) the practice of microbiological sampling of infected foci before treatment, (iii) the systematic surveillance of resistance profiles of pneumococci against antibiotics and (iv) the adequate vaccination of populations at risk.

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Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and mild cognitive impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent data sets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other data set; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale-Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<0.0001). Training with one data set and testing with another demonstrated stability between data sets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome.

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While it is now well accepted that radiolabeled antibodies can be useful for tumour detection by immunoscintigraphy, the use of larger doses of more aggressive radioisotopes coupled to antibodies for radioimmunotherapy is still in its infancy. At the experimental level, our group has shown that the intravenous injection of large doses of 131I labeled F(ab')2 fragments from monoclonal anti-carcinoembryonic antigen (CEA) antibodies can eradicate well established human colon carcinoma xenografts in nude mice. At the clinical level, in a dosimetry study performed at the Institut Gustave Roussy, the same anti-CEA monoclonal antibodies and fragments, labeled with subtherapeutic doses of 131I, were injected in patients with liver metastases from colorectal carcinomas. Direct measurement of radioactivity in surgically resected liver metastases and normal liver confirmed the specificity of tumour localization of the antibodies, but also showed that the calculated radiation doses which could be delivered by injections of 200 to 300 mCi of 131I labeled antibodies or fragments, remained fairly low, in the range of 1,500 to 3,000 rads. This is obviously insufficient for a single modality treatment. An alternative approach is to inject radiolabeled antibodies intra peritoneally to treat peritoneal carcinomatosis. Several clinical studies using this strategy are presently under evaluation and suggest that positive results can be obtained when the tumour diameters are very small. In systemic radioimmunotherapy, positive results have been obtained in more radiosensitive types of malignancies such as B cell lymphomas by intravenous injection of antibodies directed against B cell differentiation markers or against idiotypic antigens from each lymphoma, and labeled with 131I or 90Y. The major directions of research for improvement of radioimmunotherapy include the design of genetically engineered new forms of humanized antibodies, the synthesis of original chelates for coupling new radioisotopes to antibodies and the development of two step strategies for immunolocalization of radioisotopes.

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AIM: In normal aging, subjective cognitive decline (SCD) might reflect personality traits or affective states rather than objective cognitive decline. However, little is known on the correlates of SCD in mild cognitive impairment (MCI). The present study investigates SCD in MCI patients and healthy older adults, and explores the association of SCD with personality traits, affective states, behavioral and psychological symptoms (BPS), and episodic memory in patients with MCI as compared with healthy older adults. METHODS: A total of 55 patients with MCI and 84 healthy older adults were recruited. Standard instruments were used to evaluate SCD, episodic memory, BPS and affective states. Premorbid and current personality traits were assessed by proxies using the NEO Personality Inventory Revised. RESULTS: Patients with MCI generally reported SCD more often than healthy older adults. SCD was positively associated with depressive symptoms in both groups. With regard to personality, no significant relationship was found in the healthy older group, whereas agreeableness was significantly negatively related to SCD in the MCI group. No significant association was found between SCD and episodic memory. CONCLUSIONS: SCD is more prevalent in patients with MCI than in the healthy elderly, but it does not reflect an objective cognitive impairment. SCD rather echoes depressive symptoms in both patients with MCI and healthy subjects. The negative association of SCD with agreeableness observed in patients with MCI could indicate that MCI patients scoring high on the agreeableness trait would not report SCD in order to prevent their relatives worrying about their increasing cognitive difficulties. Geriatr Gerontol Int 2014; 14: 589-595.

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The expected therapeutic gain of a combined radioimmunotherapy (RIT) with conventional radiotherapy (RT) would be a synergy of tumor irradiation, provided that toxic, dose-limiting side effects concern different organs. We have shown in a model of subcutaneous human colon cancer transplants in nude mice that RIT with 131I-labeled anti-CEA antibody fragments combined with fractionated RT give an additive therapeutic effect without increase of side effects. A second study of different timing schedules of RIT and RT has shown that close association of both therapies without delay is more efficient than a therapy with a treatment-free interval of two weeks. In a new model of human colon cancer liver metastases in nude mice, early treatment with RIT and with RT has been curative, whereas therapies initiated later were less efficient, suggesting that the combined therapy is likely to be more efficient in an adjuvant situation after surgery. At the clinical level, six patients with limited liver metastatic disease from colorectal cancer were treated with RIT using 200 mCi 131I-labeled anti-CEA MAb F(ab')2 fragments combined with fractionated external beam RT of 20 Gy to the entire liver. As expected, spontaneously reversible bone marrow toxicity grade 3 to 4 and reversible liver toxicity grade 1 to 3 have been observed. By computerized tomography, three patients showed stable disease and one patient partial remission, whereas two patients had progressive disease. In conclusion, animal experiments have shown a clear advantage of combined RT and RIT, and the clinical study shows the feasibility of such a therapy in patients with colorectal cancer liver metastases.

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Aims: To describe personality traits and their changes in mild cognitive impairment (MCI) and control subjects. Methods: Sixty-three MCI and 90 control subjects were asked to describe their current personality traits by the Structured Interview for the Five-Factor Model (SIFFM). For each subject, a close relative retrospectively assessed these descriptions both as to the previous and current personality traits, using the Revised NEO Personality Inventory, Form R (NEO-PI-R). Results: Self-assessed MCI subjects reported significantly lower scores in the openness dimension than control subjects [F(1, 150) = 9.84, p = 0.002, ηp(2) = 0.06]. In current observer ratings, MCI subjects had higher scores on neuroticism [F(1, 137) = 7.55, p = 0.007, ηp(2) = 0.05] and lower ones on extraversion [F(1, 137) = 6.40, p = 0.013, ηp(2) = 0.04], openness [F(1, 137) = 9.93, p = 0.002, ηp(2) = 0.07], agreeableness [F(1, 137) = 10.18, p = 0.002, ηp(2) = 0.07] and conscientiousness [F(1, 137) = 25.96, p < 0.001, ηp(2) = 0.16]. Previous personality traits discriminated the groups as previous openness [odds ratio (OR) = 0.97, 95% confidence interval (CI) = 0.95-0.99, p = 0.014] and conscientiousness (OR = 0.96, 95% CI 0.94-0.98, p = 0.001) were negatively related to MCI group membership. In MCI subjects, conscientiousness [F(1, 137) = 19.20, p < 0.001, ηp(2) = 0.12] and extraversion [F(1, 137) = 22.27, p < 0.001, ηp(2) = 0.14] decreased between previous and current evaluations and neuroticism increased [F(1, 137) = 22.23, p < 0.001, ηp(2) = 0.14], whereas no significant change was found in control subjects. Conclusions: MCI subjects undergo significant personality changes. Thus, personality assessment may aid the early detection of dementia. © 2013 S. Karger AG, Basel.

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BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

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Recent studies have indicated that gamma band oscillations participate in the temporal binding needed for the synchronization of cortical networks involved in short-term memory and attentional processes. To date, no study has explored the temporal dynamics of gamma band in the early stages of dementia. At baseline, gamma band analysis was performed in 29 cases with mild cognitive impairment (MCI) during the n-back task. Based on phase diagrams, multiple linear regression models were built to explore the relationship between the cognitive status and gamma oscillation changes over time. Individual measures of phase diagram complexity were made using fractal dimension values. After 1 year, all cases were assessed neuropsychologically using the same battery. A total of 16 MCI patients showed progressive cognitive decline (PMCI) and 13 remained stable (SMCI). When adjusted for gamma values at lag -2, and -3 ms, PMCI cases displayed significantly lower average changes in gamma values than SMCI cases both in detection and 2-back tasks. Gamma fractal dimension of PMCI cases displayed significantly higher gamma fractal dimension values compared to SMCI cases. This variable explained 11.8% of the cognitive variability in this series. Our data indicate that the progression of cognitive decline in MCI is associated with early deficits in temporal binding that occur during the activation of selective attention processes.

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Studies assessing skin irritation to chemicals have traditionally used laboratory animals; however, such methods are questionable regarding their relevance for humans. New in vitro methods have been validated, such as the reconstructed human epidermis (RHE) model (Episkin®, Epiderm®). The comparison (accuracy) with in vivo results such as the 4-h human patch test (HPT) is 76% at best (Epiderm®). There is a need to develop an in vitro method that better simulates the anatomo-pathological changes encountered in vivo. To develop an in vitro method to determine skin irritation using human viable skin through histopathology, and compare the results of 4 tested substances to the main in vitro methods and in vivo animal method (Draize test). Human skin removed during surgery was dermatomed and mounted on an in vitro flow-through diffusion cell system. Ten chemicals with known non-irritant (heptylbutyrate, hexylsalicylate, butylmethacrylate, isoproturon, bentazon, DEHP and methylisothiazolinone (MI)) and irritant properties (folpet, 1-bromohexane and methylchloroisothiazolinone (MCI/MI)), a negative control (sodiumchloride) and a positive control (sodiumlaurylsulphate) were applied. The skin was exposed at least for 4h. Histopathology was performed to investigate irritation signs (spongiosis, necrosis, vacuolization). We obtained 100% accuracy with the HPT model; 75% with the RHE models and 50% with the Draize test for 4 tested substances. The coefficients of variation (CV) between our three test batches were <0.1, showing good reproducibility. Furthermore, we reported objectively histopathological irritation signs (irritation scale): strong (folpet), significant (1-bromohexane), slight (MCI/MI at 750/250ppm) and none (isoproturon, bentazon, DEHP and MI). This new in vitro test method presented effective results for the tested chemicals. It should be further validated using a greater number of substances; and tested in different laboratories in order to suitably evaluate reproducibility.

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We have developed a technetium labeling technology based on a new organometallic chemistry, which involves simple mixing of the novel reagent, a 99m Tc(I)-carbonyl compound, with a His-tagged recombinant protein. This method obviates the labeling of unpaired engineered cysteines, which frequently create problems in large-scale expression and storage of disulfide-containing proteins. In this study, we labeled antibody single-chain Fv fragments to high specific activities (90 mCi/mg), and the label was very stable to serum and all other challenges tested. The pharmacokinetic characteristics were indistinguishable from iodinated scFv fragments, and thus scFV fragments labeled by the new method will be suitable for biodistribution studies. This novel labeling method should be applicable not only to diagnostic imaging with 99mTc, but also to radioimmunotherapy approaches with 186/188 Re, and its use can be easily extended to almost any recombinant protein or synthetic peptide.

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The three most frequent forms of mild cognitive impairment (MCI) are single-domain amnestic MCI (sd-aMCI), single-domain dysexecutive MCI (sd-dMCI) and multiple-domain amnestic MCI (md-aMCI). Brain imaging differences among single domain subgroups of MCI were recently reported supporting the idea that electroencephalography (EEG) functional hallmarks can be used to differentiate these subgroups. We performed event-related potential (ERP) measures and independent component analysis in 18 sd-aMCI, 13 sd-dMCI and 35 md-aMCI cases during the successful performance of the Attentional Network Test. Sensitivity and specificity analyses of ERP for the discrimination of MCI subgroups were also made. In center-cue and spatial-cue warning stimuli, contingent negative variation (CNV) was elicited in all MCI subgroups. Two independent components (ICA1 and 2) were superimposed in the time range on the CNV. The ICA2 was strongly reduced in sd-dMCI compared to sd-aMCI and md-aMCI (4.3 vs. 7.5% and 10.9% of the CNV component). The parietal P300 ERP latency increased significantly in sd-dMCI compared to md-aMCI and sd-aMCI for both congruent and incongruent conditions. This latency for incongruent targets allowed for a highly accurate separation of sd-dMCI from both sd-aMCI and md-aMCI with correct classification rates of 90 and 81%, respectively. This EEG parameter alone performed much better than neuropsychological testing in distinguishing sd-dMCI from md-aMCI. Our data reveal qualitative changes in the composition of the neural generators of CNV in sd-dMCI. In addition, they document an increased latency of the executive P300 component that may represent a highly accurate hallmark for the discrimination of this MCI subgroup in routine clinical settings.

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River bifurcations are key nodes within braided river systems controlling the flow and sediment partitioning and therefore the dynamics of the river braiding process. Recent research has shown that certain geometrical configurations induce instabilities that lead to downstream mid-channel bar formation and the formation of bifurcations. However, we currently have a poor understanding of the flow division process within bifurcations and the flow dynamics in the downstream bifurcates, both of which are needed to understand bifurcation stability. This paper presents results of a numerical sensitivity experiment undertaken using computational fluid dynamics (CFD) with the purpose of understanding the flow dynamics of a series of idealized bifurcations. A geometric sensitivity analysis is undertaken for a range of channel slopes (0.005 to 0.03), bifurcation angles (22 degrees to 42 degrees) and a restricted set of inflow conditions based upon simulating flow through meander bends with different curvature on the flow field dynamics through the bifurcation. The results demonstrate that the overall slope of the bifurcation affects the velocity of flow through the bifurcation and when slope asymmetry is introduced, the flow structures in the bifurcation are modified. In terms of bifurcation evolution the most important observation appears to be that once slope asymmetry is greater than 0.2 the flow within the steep bifurcate shows potential instability and the potential for alternate channel bar formation. Bifurcation angle also defines the flow structures within the bifurcation with an increase in bifurcation angle increasing the flow velocity down both bifurcates. However, redistributive effects of secondary circulation caused by upstream curvature can very easily counter the effects of local bifurcation characteristics. Copyright (C) 2011 John Wiley & Sons, Ltd.

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Purpose: To report the findings of the clinical and molecular evaluation in a Greek family with fleck corneal dystrophy (CFD).Methods: A 58-year-old woman was seen on routine ophthalmic examination and diagnosed as having CFD. All available family members were examined to evaluate the clinical findings and inheritance of the disease. Twenty members of the family in five generations underwent slit-lamp examination. Eleven were females and nine males, aged from two years to 85 years old. Blood samples were available from four patients with CFD and seven unaffected relatives, and the DNAs were subjected to molecular screening of the phosphoinositide kinase, five finger-containing (PIKFYVE) gene by direct sequencing or denaturing high performance liquid chromatography (DHPLC).Results: The clinical evaluation revealed six family members (five females and one male) with CFD. In two CFD patients early cataract formation was noticed. All patients affected with the corneal dystrophy were asymptomatic. The molecular analyses demonstrated the existence of a novel c. 3060-3063delCCTT (p.P968Vfs23) mutation in PIKFYVE in all CFD patients tested but in none of the six unaffected family members. No molecular screening was performed in the seventh unaffected member as the causative mutation was clearly transmitted from his affected wife to his affected son.Conclusions: We report on the clinical and molecular findings of a five generation Greek family with CFD and we conclude that the novel c. 3060-3063delCCTT (p. P968Vfs23) mutation in PIKFYVE, which segregated with the disease, was the causative mutation in this family.

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Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease.

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Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.