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A new species of the basal araneomorph spider genus Ectatosticta (Araneae, Hypochilidae) from China
(2009)
The hypochilid spider Ectatosticta davidi (Simon) is redescribed on the basis of adults from Mt. Taibaishan in Shaanxi Province, China; the specimens from Qinghai Province previously identified as E. davidi by most modern authors belong to a new species described as E. deltshevi. Keywords: Araneae, Araneomorphae, Hypochilidae, Ectatosticta, China
Despite prevailing arid conditions, the diversity of terrestrial and freshwater biota in the Middle East is amazingly high and marine biodiversity is among the highest on Earth. Th roughout the Region, threats to the environment are moderate to severe. Despite the outstanding economic and ecological importance of biological diversity, the capacity in biodiversity-related research and academic education is inadequate. The "Middle Eastern Biodiversity Network" (MEBN), founded in 2006 by six universities and research institutes in Iran, Jordan, Germany, Lebanon and Yemen was designed to fi ll this gap. An integrated approach is taken to upgrade biodiversity research and education in order to improve regional ecosystem conservation and management capacities. A wide range of activities are carried out in the framework of the Network, including capacity building in biological collection management and professional natural history curatorship, developing university curricula in biodiversity, conducting scientifi c research, organising workshops and conferences on Middle Eastern biodiversity, and translating the results of biodiversity research into conservation and sustainable development. Keywords: Middle Eastern biodiversity, nature museums, biodiversity research, biodiversity education, biodiversity conservation, biodiversity networks
Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.
Short-term memory requires the coordination of sub-processes like encoding, retention, retrieval and comparison of stored material to subsequent input. Neuronal oscillations have an inherent time structure, can effectively coordinate synaptic integration of large neuron populations and could therefore organize and integrate distributed sub-processes in time and space. We observed field potential oscillations (14–95 Hz) in ventral prefrontal cortex of monkeys performing a visual memory task. Stimulus-selective and performance-dependent oscillations occurred simultaneously at 65–95 Hz and 14–50 Hz, the latter being phase-locked throughout memory maintenance. We propose that prefrontal oscillatory activity may be instrumental for the dynamical integration of local and global neuronal processes underlying short-term memory.
Experience-driven formation of parts-based representations in a model of layered visual memory
(2009)
Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces. Keywords: visual memory, self-organization, unsupervised learning, competitive learning, bidirectional plasticity, activity homeostasis, parts-based representation, cortical column
Echocardiography is increasingly used in the management of the critically ill patient as a non-invasive diagnostic and monitoring tool. Whilst in few countries specialized national training schemes for intensive care unit (ICU) echocardiography have been developed, specific guidelines for ICU physicians wishing to incorporate echocardiography into their clinical practice are lacking. Further, existing echocardiography accreditation does not reflect the requirements of the ICU practitioner. The WINFOCUS (World Interactive Network Focused On Critical UltraSound) ECHO-ICU Group drew up a document aimed at providing guidance to individual physicians, trainers and the relevant societies of the requirements for the development of skills in echocardiography in the ICU setting. The document is based on recommendations published by the Royal College of Radiologists, British Society of Echocardiography, European Association of Echocardiography and American Society of Echocardiography, together with international input from established practitioners of ICU echocardiography. The recommendations contained in this document are concerned with theoretical basis of ultrasonography, the practical aspects of building an ICU-based echocardiography service as well as the key components of standard adult TTE and TEE studies to be performed on the ICU. Specific issues regarding echocardiography in different ICU clinical scenarios are then described. Obtaining competence in ICU echocardiography may be achieved in different ways – either through completion of an appropriate fellowship/training scheme, or, where not available, via a staged approach designed to train the practitioner to a level at which they can achieve accreditation. Here, peri-resuscitation focused echocardiography represents the entry level – obtainable through established courses followed by mentored practice. Next, a competence-based modular training programme is proposed: theoretical elements delivered through blended-learning and practical elements acquired in parallel through proctored practice. These all linked with existing national/international echocardiography courses. When completed, it is anticipated that the practitioner will have performed the prerequisite number of studies, and achieved the competency to undertake accreditation (leading to Level 2 competence) via a recognized National or European examination and provide the appropriate required evidence of competency (logbook). Thus, even where appropriate fellowships are not available, with support from the relevant echocardiography bodies, training and subsequently accreditation in ICU echocardiography becomes achievable within the existing framework of current critical care and cardiological practice, and is adaptable to each countrie's needs.
Background: Local adaptation to divergent environmental conditions can promote population genetic differentiation even in the absence of geographic barriers and hence, lead to speciation. Perturbations by catastrophic events, however, can distort such parapatric ecological speciation processes. Here, we asked whether an exceptionally strong flood led to homogenization of gene pools among locally adapted populations of the Atlantic molly (Poecilia mexicana, Poeciliidae) in the Cueva del Azufre system in southern Mexico, where two strong environmental selection factors (darkness within caves and/or presence of toxic H2S in sulfidic springs) drive the diversification of P. mexicana. Nine nuclear microsatellites as well as heritable female life history traits (both as a proxy for quantitative genetics and for trait divergence) were used as markers to compare genetic differentiation, genetic diversity, and especially population mixing (immigration and emigration) before and after the flood. Results: Habitat type (i.e., non-sulfidic surface, sulfidic surface, or sulfidic cave), but not geographic distance was the major predictor of genetic differentiation. Before and after the flood, each habitat type harbored a genetically distinct population. Only a weak signal of individual dislocation among ecologically divergent habitat types was uncovered (with the exception of slightly increased dislocation from the Cueva del Azufre into the sulfidic creek, El Azufre). By contrast, several lines of evidence are indicative of increased flood-induced dislocation within the same habitat type, e.g., between different cave chambers of the Cueva del Azufre. Conclusions: The virtual absence of individual dislocation among ecologically different habitat types indicates strong natural selection against migrants. Thus, our current study exemplifies that ecological speciation in this and other systems, in which extreme environmental factors drive speciation, may be little affected by temporary perturbations, as adaptations to physico-chemical stressors may directly affect the survival probability in divergent habitat types.
Background: Thymostimulin is a thymic peptide fraction with immune-mediated cytotoxicity against hepatocellular carcinoma (HCC) in vitro and palliative efficacy in advanced HCC in two independent phase II trials. The aim of this study was to assess the efficacy of thymostimulin in a phase III trial. Methods: The study was designed as a prospective randomised, placebo-controlled, double-blind, multicenter clinical phase III trial. Between 10/2002 and 03/2005, 135 patients with locally advanced or metastasised HCC (Karnofsky [greater than or equal to]60% / Child-Pugh [less than or equal to]12) were randomised to receive thymostimulin 75 mg s.c. 5x/week or placebo stratified according to liver function. Primary endpoint was twelve-month survival, secondary endpoints overall survival (OS), time to progression (TTP), tumor response, safety and quality of life. A subgroup analysis according to liver function, KPS and tumor stage (Okuda, CLIP and BCLC) formed part of the protocol. Current Controlled Trials ISRCTN64487365. Results: Twelve-month survival was 28% [95%CI 17-41; treatment] and 32% [95%CI 19-44; control] with no significant differences in median OS (5.0 [95% CI 3.7-6.3] vs. 5.2 [95% CI 3.5-6.9] months; p=0.87, HR=1.04 [95% CI 0.7-1.6]) or TTP (5.3 [95%CI 2.0-8.6] vs. 2.9 [95%CI 2.6-3.1] months; p=0.60, HR=1.13 [95% CI 0.7-1.8]). Adjustment for liver function, Karnofsky status or tumor stage did not affect results. While quality of life was similar in both groups, fewer patients on thymostimulin suffered from accumulating ascites and renal failure. Conclusions: In our phase III trial, we found no evidence of any benefit to thymostimulin in the treatment of advanced HCC and there is therefore no justification for its use as single-agent treatment. The effect of thymostimulin on hepato-renal function requires further confirmation. trial registration: Current Controlled Trials ISRCTN64487365
Background: Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are produced during hemorrhagic shock and resuscitation (H/R), which may contribute to multiple organ failure. The AIM of this study was to test the hypothesis that green tea (Camellia sinenesis) extract containing 85% polyphenols decreases injury after H/R in rats by scavenging ROS and RNS. Method: S: Female Sprague Dawley rats were given 100 mg polyphenol extract/kg body weight or vehicle 2 h prior to hemorrhagic shock. H/R was induced by two protocols: 1) withdrawal of blood to a mean arterial pressure of 40 mm Hg followed by further withdrawals to decrease blood pressure progressively to 28 mm Hg over 1 h (severe), and 2) withdrawal of blood to a sustained hypotension of 40 mm Hg for 1 h (moderate). Rats were then resuscitated over 1 h with 60% of the shed blood volume plus twice the shed blood volume of lactated Ringer's solution. Serum samples were collected at 10 min and 2 h after resuscitation. At 2 or 18 h, livers were harvested for cytokine and 3-nitrotyrosine quantification, immunohistochemical detection of 4-hydroxynonenol (4-HNE) and inducible nitric oxide synthase (iNOS) protein expression. Results: After severe H/R, 18-h survival increased from 20% after vehicle to 70% after polyphenols (p<0.05). After moderate H/R, survival was greater (80%) and not different between vehicle and polyphenols. In moderate H/R, serum alanine aminotransferase (ALT) increased at 10 min and 2 h postresuscitation to 345 and 545 IU/L, respectively. Polyphenol treatment blunted this increase to 153 and 252 IU/L at 10 min and 2 h (p<0.01). Polyphenols also blunted increases in liver homogenates of TNFalpha (7.0 pg/mg with vehicle vs. 4.9 pg/mg with polyphenols, p<0.05), IL-1beta (0.80 vs. 0.37 pg/mg, p<0.05), IL-6 (6.9 vs. 5.1 pg/mg, p<0.05) and nitrotyrosine (1.9 pg/mg vs. 0.6 pg/mg, p<0.05) measured 18 h after H/R. Hepatic 4-HNE immunostaining indicative of lipid peroxidation also decreased from 4.8% after vehicle to 1.5% after polyphenols (p<0.05). By contrast, polyphenols did not block increased iNOS expression at 2 h after H/R. CONCLUSION: Polyphenols decrease ROS/RNS formation and are beneficial after hemorrhagic shock and resuscitation.
Background: Because Endomyocardial Biopsy has low sensitivity of about 20%, it can be performed near to myocardium that presented as Late Gadolinium Enhancement (LGE) in cardiovascular magnetic resonance (CMR). However the important issue of comparing topography of CMR and histological findings has not yet been investigated. Thus the current study was performed using an animal model of myocarditis. Results: In 10 male Lewis rats Experimental Autoimmune myocarditis was induced, 10 rats served as control. On day 21 animals were examined by CMR to compare topographic distribution of LGE to histological inflammation. Sensitivity, specificity, positive and negative predictive values for LGE in diagnosing myocarditis were determined for each segment of myocardium. Latter diagnostic values varied widely depending on topographic distribution of LGE and inflammation as well as on the used CMR sequence. Sensitivity of LGE was up to 76% (left lateral myocardium) and positive predictive values were up to 85% (left lateral myocardium), whereas sensitivity and positive predictive value dropped to 0 - 33% (left inferior myocardium). Conclusions: Topographic distribution of LGE and histological inflammation seem to influence sensitivity, specifity, positive and negative predictive values. Nevertheless, positive predictive value for LGE of up to 85% indicates that Endomyocardial Biopsy should be performed "MR-guided". LGE seems to have greater sensitivity than Endomyocardial Biopsy for the diagnosis of myocarditis.
Since the description of sepsis by Schottmüller in 1914, the amount on knowledge available on sepsis and its underlying pathophysiology has substantially increased. Epidemiologic examinations of abdominal septic shock patients show the potential for high risk posed by and the extensive therapy situation in the intensive care unit (ICU) (5). Unfortunately, until now it has not been possible to significantly reduce the mortality rate of septic shock, which is as high as 50-60% worldwide, although PROWESS' results (1) are encouraging. This paper summarizes the main results of the MEDAN project and their medical impacts. Several aspects are already published, see the references. The heterogeneity of patient groups and the variations in therapy strategies is seen as one of the main problems for sepsis trials. In the MEDAN multi-center study of 71 intensive care units in Germany, a group of 382 patients made up exclusively of abdominal septic shock patients who met the consensus criteria for septic shock (3) was analysed. For use within scores or stand-alone experiments variables are often studied as isolated variables, not as a multidimensional whole, e.g. a recent study takes a look at the role thrombocytes play (15). To avoid this limitation, our study compares several established scores (SOFA, APACHE II, SAPS II, MODS) by a multi-dimensional neuronal network analysis. For outcome prediction the data of 382 patients was analysed by using most of the commonly documented vital parameters and doses of medicine (metric variables). Data was collected in German hospitals from 1998 to 2001. The 382 handwritten patient records were transferred to an electronic database giving the amount of 2.5 million data entries. The metric data contained in the database is composed of daily measurements and doses of medicine. We used range and plausibility checks to allow no faulty data in the electronic database. 187 of the 382 patients are deceased (49 %).
Attraction and commercial success of web sites depend heavily on the additional values visitors may find. Here, individual, automatically obtained and maintained user profiles are the key for user satisfaction. This contribution shows for the example of a cooking information site how user profiles might be obtained using category information provided by cooking recipes. It is shown that metrical distance functions and standard clustering procedures lead to erroneous results. Instead, we propose a new mutual information based clustering approach and outline its implications for the example of user profiling.
Data driven automatic model selection and parameter adaptation – a case study for septic shock
(2004)
In bioinformatics, biochemical pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically learning the parameters is necessary. This paper propose as model selection criterion the least complex description of the observed data by the model, the minimum description length. For the small, but important example of inflammation modeling the performance of the approach is evaluated.
In bioinformatics, biochemical signal pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically obtaining the most appropriate model and learning its parameters is extremely interesting. One of the most often used approaches for model selection is to choose the least complex model which “fits the needs”. For noisy measurements, the model which has the smallest mean squared error of the observed data results in a model which fits too accurately to the data – it is overfitting. Such a model will perform good on the training data, but worse on unknown data. This paper propose as model selection criterion the least complex description of the observed data by the model, the minimum description length. For the small, but important example of inflammation modeling the performance of the approach is evaluated. Keywords: biochemical pathways, differential equations, septic shock, parameter estimation, overfitting, minimum description length.
In bioinformatics, biochemical pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically learning the parameters is necessary. In this paper, for the small, important example of inflammation modeling a network is constructed and different learning algorithms are proposed. It turned out that due to the nonlinear dynamics evolutionary approaches are necessary to fit the parameters for sparse, given data. Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence - ICTAI 2003
In bioinformatics, biochemical pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically learning the parameters is necessary. In this paper, for the small, important example of inflammation modeling a network is constructed and different learning algorithms are proposed. It turned out that due to the nonlinear dynamics evolutionary approaches are necessary to fit the parameters for sparse, given data. Keywords: model parameter adaption, septic shock. coupled differential equations, genetic algorithm.
In contrast to the symbolic approach, neural networks seldom are designed to explain what they have learned. This is a major obstacle for its use in everyday life. With the appearance of neuro-fuzzy systems which use vague, human-like categories the situation has changed. Based on the well-known mechanisms of learning for RBF networks, a special neuro-fuzzy interface is proposed in this paper. It is especially useful in medical applications, using the notation and habits of physicians and other medically trained people. As an example, a liver disease diagnosis system is presented.
The prevention of credit card fraud is an important application for prediction techniques. One major obstacle for using neural network training techniques is the high necessary diagnostic quality: Since only one financial transaction of a thousand is invalid no prediction success less than 99.9% is acceptable. Due to these credit card transaction proportions complete new concepts had to be developed and tested on real credit card data. This paper shows how advanced data mining techniques and neural network algorithm can be combined successfully to obtain a high fraud coverage combined with a low false alarm rate.
This paper describes the use of a Radial Basis Function (RBF) neural network in the approximation of process parameters for the extrusion of a rubber profile in tyre production. After introducing the rubber industry problem, the RBF network model and the RBF net learning algorithm are developed, which uses a growing number of RBF units to compensate the approximation error up to the desired error limit. Its performance is shown for simple analytic examples. Then the paper describes the modelling of the industrial problem. Simulations show good results, even when using only a few training samples. The paper is concluded by a discussion of possible systematic error influences, improvements and potential generalisation benefits. Keywords: Adaptive process control; Parameter estimation; RBF-nets; Rubber extrusion
In this paper we regard first the situation where parallel channels are disturbed by noise. With the goal of maximal information conservation we deduce the conditions for a transform which "immunizes" the channels against noise influence before the signals are used in later operations. It shows up that the signals have to be decorrelated and normalized by the filter which corresponds for the case of one channel to the classical result of Shannon. Additional simulations for image encoding and decoding show that this constitutes an efficient approach for noise suppression. Furthermore, by a corresponding objective function we deduce the stochastic and deterministic learning rules for a neural network that implements the data orthonormalization. In comparison with other already existing normalization networks our network shows approximately the same in the stochastic case but, by its generic deduction ensures the convergence and enables the use as independent building block in other contexts, e.g. whitening for independent component analysis. Keywords: information conservation, whitening filter, data orthonormalization network, image encoding, noise suppression.