57 resultados para 170205 Neurocognitive Patterns and Neural Networks
Resumo:
A survey of starter and probiotic cultures was carried out to determine the current antibiotic resistance situation in microbial food additives in Switzerland. Two hundred isolates from 90 different sources were typed by molecular and other methods to belong to the genera Lactobacillus (74 samples), Staphylococcus (33 samples), Bifidobacterium (6 samples), Pediococcus (5 samples), or were categorized as lactococci or streptococci (82 samples). They were screened for phenotypic resistances to 20 antibiotics by the disk diffusion method. Twenty-seven isolates exhibiting resistances that are not an intrinsic feature of the respective genera were further analyzed by microarray hybridization as a tool to trace back phenotypic resistances to specific genetic determinants. Their presence was finally verified by PCR amplification or Southern hybridization. These studies resulted in the detection of the tetracycline resistance gene tet(K) in 5 Staphylococcus isolates used as meat starter cultures, the tetracycline resistance gene tet(W) in the probiotic cultures Bifidobacterium lactis DSM 10140 and Lactobacillus reuteri SD 2112 (residing on a plasmid), and the lincosamide resistance gene lnu(A) (formerly linA) in L. reuteri SD 2112.
Resumo:
BACKGROUND: Complementary and alternative medicine (CAM) and most of all anthroposophic medicine (AM) are important features of cancer treatment in Switzerland. While the number of epidemiological investigations into the use of such therapies is increasing, there is a distinct lack of reports regarding the combination of conventional and CAM methods. PATIENTS AND METHODS: 144 in-patients with advanced epithelial cancers were enrolled in a prospective quality-of-life (QoL) study at the Lukas Klinik (LK), Arlesheim, Switzerland. Tumor-related treatment was assessed 4 months prior to admission, during hospitalization and 4 months after baseline. OBJECTIVE: We aimed at giving a detailed account of conventional, AM and CAM treatment patterns in palliative care, before, during and after hospitalization, with emphasis on compliance with AM after discharge. RESULTS: Certain conventional treatments featured less during hospitalization than before but were resumed after discharge (chemotherapy, radiotherapy, sleeping pills, psychoactive drugs). Hormone therapy, corticosteroids, analgesics WHO III and antidepressants remained constant. AM treatment consisted of Iscador? (mistletoe), other plant- or mineral-derived medication, baths, massage, eurythmy, art therapy, counseling and lactovegetarian diet. Compliance after discharge was highest with Iscador (90%) and lowest with art therapy (14%). Many patients remained in the care of AM physicians. Other CAM and psychological methods were initially used by 39.9% of patients. After 4 months, the use had decreased with few exceptions. CONCLUSION: During holistic palliative treatment in an anthroposophic hospital, certain conventional treatments featured less whereas others remained constant. After discharge, chemotherapy returned to previous levels, AM compliance remained high, the use of other CAM therapies low.
Resumo:
The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.
Resumo:
The apolipoprotein E (APOE) epsilon4 allele is the major genetic risk factor for Alzheimer's disease, but an APOE effect on memory performance and memory-related neurophysiology in young, healthy subjects is unknown. We found an association of APOE epsilon4 with better episodic memory compared with APOE epsilon2 and epsilon3 in 340 young, healthy persons. Neuroimaging was performed in a subset of 34 memory-matched individuals to study genetic effects on memory-related brain activity independently of differential performance. E4 carriers decreased brain activity over 3 learning runs, whereas epsilon2 and epsilon3 carriers increased activity. This smaller neural investment of epsilon4 carriers into learning reappeared during retrieval: epsilon4 carriers exhibited reduced retrieval-related activity with equal retrieval performance. APOE isoforms had no differential effects on cognitive measures other than memory, brain volumes, and brain activity related to working memory. We suggest that APOE epsilon4 is associated with good episodic memory and an economic use of memory-related neural resources in young, healthy humans.