Fiberoptic system for recording dendritic calcium signals in layer 5 neocortical pyramidal cells in freely moving rats

Calcium influx into the dendritic tufts of layer 5 neocortical pyramidal neurons modifies a number of important cellular mechanisms. It can trigger local synaptic plasticity and switch the firing properties from regular to burst firing. Due to methodological limitations, our knowledge about Ca2+ spikes in the dendritic tuft stems mostly from in vitro experiments. However, it has been speculated that regenerative Ca2+ events in the distal dendrites correlate with distinct behavioral states. Therefore it would be most desirable to be able to record these Ca2+ events in vivo, preferably in the behaving animal. Here, we present a novel approach for recording Ca2+ signals in the dendrites of populations of layer 5 pyramidal neurons in vivo, which ensures that all recorded fluorescence changes are due to intracellular Ca2+ signals in the apical dendrites. The method has two main features: 1) bolus loading of layer 5 with a membrane-permeant Ca2+ dye resulting in specific loading of pyramidal cell dendrites in the upper layers and 2) a fiberoptic cable attached to a gradient index lens and a prism reflecting light horizontally at 90 degrees to the angle of the apical dendrites. We demonstrate that the in vivo signal-to-noise ratio recorded with this relatively inexpensive and easy-to-implement fiberoptic-based device is comparable to conventional camera-based imaging systems used in vitro. In addition, the device is flexible and lightweight and can be used for recording Ca2+ signals in the distal dendritic tuft of freely behaving animals.

Perspectives on periodontal risk factors

The development of a clinical decision tree based on knowledge about risks and reported outcomes of therapy is a necessity for successful planning and outcome of periodontal therapy. This requires a well-founded knowledge of the disease entity and a broad knowledge of how different risk conditions attribute to periodontitis. The infectious etiology, a complex immune response, and influence from a large number of co-factors are challenging conditions in clinical periodontal risk assessment. The difficult relationship between independent and dependent risk conditions paired with limited information on periodontitis prevalence adds to difficulties in periodontal risk assessment. The current information on periodontitis risk attributed to smoking habits, socio-economic conditions, general health and subjects' self-perception of health, is not comprehensive, and this contributes to limited success in periodontal risk assessment. New models for risk analysis have been advocated. Their utility for the estimation of periodontal risk assessment and prognosis should be tested. The present review addresses several of these issues associated with periodontal risk assessment.

Assessing visual disturbance conditions on the Custer National Forest

Assessment of soil disturbance on the Custer National Forest was conducted during two summers to determine if the U.S. Forest Service Forest Soil Disturbance Monitoring Protocol (FSDMP) was able to distinguish post-harvest soil conditions in a chronological sequence of sites harvested using different ground-based logging systems. Results from the first year of sampling suggested that the FSDMP point sampling method may not be sensitive enough to measure post-harvest disturbance in stands with low levels of disturbance. Therefore, a revised random transect method was used during the second sampling season to determine the actual extent of soil disturbance in these cutting units. Using combined data collected from both summers I detected statistically significant differences (p < 0.05) in fine fraction bulk density measurements between FSDMP disturbance classes across all sites. Disturbance class 3 (most severe) had the highest reported bulk density, which suggest that the FSDMP visual class estimates are defined adequately allowing for correlations to be made between visual disturbance and actual soil physical characteristics. Forest site productivity can be defined by its ability to retain carbon and convert it to above- and belowground biomass. However, forest management activities that alter basic site characteristics have the potential to alter productivity. Soil compaction is one critical management impact that is important to understand; compaction has been shown to impede the root growth potential of plants, reduce water infiltration rates increasing erosion potential, and alter plant available water and nutrients, depending on soil texture. A new method to assess ground cover, erosion, and other soil disturbances was recently published by the U.S. Forest Service, as the Forest Soil Disturbance Protocol (FSDMP). The FSDMP allows soil scientists to visually assign a disturbance class estimate (0 – none, 1, 2, 3 – severe) from field measures of consistently defined soil disturbance indicators (erosion, fire, rutting, compaction, and platy/massive/puddled structure) in small circular (15 cm) plots to compare soil quality properties pre- and post- harvest condition. Using this protocol we were able to determine that ground-based timber harvesting activities occurring on the Custer National Forest are not reaching the 15% maximum threshold for detrimental soil disturbance outlined by the Region 1 Soil Quality Standards.

Promotion of health in older people: a randomised controlled trial of health risk appraisal in British general practice

BACKGROUND: there is inadequate evidence to support currently formulated NHS strategies to achieve health promotion and preventative care in older people through broad-based screening and assessment in primary care. The most extensively evaluated delivery instrument for this purpose is Health Risk Appraisal (HRA). This article describes a trial using HRA to evaluate the effect on health behaviour and preventative-care uptake in older people in NHS primary care. METHODS: a randomised controlled trial was undertaken in three London primary care group practices. Functionally independent community-dwelling patients older than 65 years (n = 2,503) received a self-administered Health Risk Appraisal for Older Persons (HRA-O) questionnaire leading to computer-generated individualised written feedback to participants and general practitioners (GPs), integrated into practice information-technology (IT) systems. All primary care staff received training in preventative health in older people. The main outcome measures were self-reported health behaviour and preventative care uptake at 1-year follow-up. RESULTS: of 2,503 individuals randomised, 2,006 respondents (80.1%) (intervention, n = 940, control n = 1,066) were available for analysis. Intervention group respondents reported slightly higher pneumococcal vaccination uptake and equivocal improvement in physical activity levels compared with controls. No significant differences were observed for any other categories of health behaviour or preventative care measures at 1-year follow-up. CONCLUSIONS: HRA-O implemented in this way resulted in minimal improvement of health behaviour or uptake of preventative care measures in older people. Supplementary reinforcement involving contact by health professionals with patients over and above routine clinical encounters may be a prerequisite to the effectiveness of IT-based delivery systems for health promotion in older people.

Libre Courseware For Bayesian Decision Making

This paper describes the ideas and problems of the Edukalibre e-learning project, in which the author takes part. The basic objective of the project shares the development and exploitation of software components for web-based information systems applied to education as well as organizing of teaching material for them. The paper concerns a problem of the mathematical-oriented courseware and describes the experience in developing LaTeX-supporting online converting tool.

Genomewide association for a dominant pigmentation gene in sheep

Most published genomewide association studies (GWAS) in sheep have investigated recessively inherited monogenic traits. The objective here was to assess the feasibility of performing GWAS for a dominant trait for which the genetic basis was already known. A total of 42 Manchega and Rasa Aragonesa sheep that segregate solid black or white coat pigmentation were genotyped using the SNP50 BeadChip. Previous analysis in Manchegas demonstrated a complete association between the pigmentation trait and alleles of the MC1R gene, setting an a priori expectation for GWAS. Multiple methods were used to identify and quantify the strength of population substructure between black and white animals, before allelic association testing was performed for 49 034 SNPs. Following correction for substructure, GWAS identified the most strongly associated SNP (s26449) was also the closest to the MC1R gene. The finding was strongly supported by the permutation tree-based random forest (RF) analysis. Importantly, GWAS identified unlinked SNP with only slightly lower p-values than for s26449. Random forest analysis indicated these were false positives, suggesting interpretation based on both approaches was beneficial. The results indicate that a combined analytical approach can be successful in studies where a modest number of animals are available and substantial population stratification exists.

Comparative enzymology of 11beta-hydroxysteroid dehydrogenase type 1 from six species.

11beta-Hydroxysteroid dehydrogenase type 1 (11beta-HSD1), catalyzing the intracellular activation of cortisone to cortisol, is currently considered a promising target to treat patients with metabolic syndrome; hence, there is considerable interest in the development of selective inhibitors. For preclinical tests of such inhibitors, the characteristics of 11beta-HSD1 from the commonly used species have to be known. Therefore, we determined differences in substrate affinity and inhibitor effects for 11beta-HSD1 from six species. The differences in catalytic activities with cortisone and 11-dehydrocorticosterone were rather modest. Human, hamster and guinea-pig 11beta-HSD1 displayed the highest catalytic efficiency in the oxoreduction of cortisone, while mouse and rat showed intermediate and dog the lowest activity. Murine 11beta-HSD1 most efficiently reduced 11-dehydrocorticosterone, while the enzyme from dog showed lower activity than those from the other species. 7-ketocholesterol (7KC) was stereospecifically converted to 7beta-hydroxycholesterol by recombinant 11beta-HSD1 from all species analyzed except hamster, which showed a slight preference for the formation of 7alpha-hydroxycholesterol. Importantly, guinea-pig and canine 11beta-HSD1 displayed very low 7-oxoreductase activities. Furthermore, we demonstrate significant species-specific variability in the potency of various 11beta-HSD1 inhibitors, including endogenous compounds, natural chemicals and pharmaceutical compounds. The results suggest significant differences in the three-dimensional organization of the hydrophobic substrate-binding pocket of 11beta-HSD1, and they emphasize that species-specific variability must be considered in the interpretation of results obtained from different animal experiments. The assessment of such differences, by cell-based test systems, may help to choose the appropriate animal for safety and efficacy studies of novel potential drug candidates.

Influence of hormone replacement therapy on proteomic pattern in serum of postmenopausal women

OBJECTIVES: Proteomics approaches to cardiovascular biology and disease hold the promise of identifying specific proteins and peptides or modification thereof to assist in the identification of novel biomarkers. METHOD: By using surface-enhanced laser desorption and ionization time of flight mass spectroscopy (SELDI-TOF-MS) serum peptide and protein patterns were detected enabling to discriminate between postmenopausal women with and without hormone replacement therapy (HRT). RESULTS: Serum of 13 HRT and 27 control subjects was analyzed and 42 peptides and proteins could be tentatively identified based on their molecular weight and binding characteristics on the chip surface. By using decision tree-based Biomarker Patternstrade mark Software classification and regression analysis a discriminatory function was developed allowing to distinguish between HRT women and controls correctly and, thus, yielding a sensitivity of 100% and a specificity of 100%. The results show that peptide and protein patterns have the potential to deliver novel biomarkers as well as pinpointing targets for improved treatment. The biomarkers obtained represent a promising tool to discriminate between HRT users and non-users. CONCLUSION: According to a tentative identification of the markers by their molecular weight and binding characteristics, most of them appear to be part of the inflammation induced acute-phase response

Grazing behaviour, physical activity and metabolic profile of two Holstein strains in an organic grazing system

The challenge for sustainable organic dairy farming is identification of cows that are well adapted to forage-based production systems. Therefore, the aim of this study was to compare the grazing behaviour, physical activity and metabolic profile of two different Holstein strains kept in an organic grazing system without concentrate supplementation. Twelve Swiss (HCH ; 566 kg body weight (BW) and 12 New Zealand Holstein-Friesian (HNZ ; 530 kg BW) cows in mid-lactation were kept in a rotational grazing system. After an adaptation period, the milk yield, nutrient intake, physical activity and grazing behaviour were recorded for each cow for 7 days. On three consecutive days, blood was sampled at 07:00, 12:00 and 17:00 h from each cow by jugular vein puncture. Data were analysed using linear mixed models. No differences were found in milk yield, but milk fat (3.69 vs. 4.05%, P = 0.05) and milk protein percentage (2.92 vs. 3.20%, P < 0.01) were lower in HCH than in HNZ cows. Herbage intake did not differ between strains, but organic matter digestibility was greater (P = 0.01) in HCH compared to HNZ cows. The HCH cows spent less (P = 0.04) time ruminating (439 vs. 469 min/day) and had a lower (P = 0.02) number of ruminating boli when compared to the HNZ cows. The time spent eating and physical activity did not differ between strains. Concentrations of IGF-1 and T3 were lower (P ≤ 0.05) in HCH than HNZ cows. In conclusion, HCH cows were not able to increase dry matter intake in order to express their full genetic potential for milk production when kept in an organic grazing system without concentrate supplementation. On the other hand, HNZ cows seem to compensate for the reduced nutrient availability better than HCH cows but could not use that advantage for increased production efficiency

Galileo Orbit and Clock Quality of the IGS Multi-GNSS Experiment

The Multi-GNSS Experiment (MGEX) of the International GNSS Service (IGS) aims at the data collection and analysis of all available satellite navigation systems. In particular the new global and regional satellite navigation systems are of interest, i.e., the European Galileo, the Chinese BeiDou, the Japanese QZSS as well as satellite based augmentation systems. This article analyzes the orbit and clock quality of the Galileo products of four MGEX analysis centers for a common time period of 20 weeks. Orbit comparisons of the individual analysis centers have a consistency at the 5–30 cm level. Day boundary discontinuities range from 4 to 28 cm whereas 2-day orbit fit RMS values vary between 1 and 7 cm. The accuracy evaluated by satellite laser ranging residuals is on the one decimeter level with a systematic bias of about −5 cm for all analysis centers. In addition, systematic errors on the decimeter level related to solar radiation pressure mismodeling are present in all orbit products. Due to the correlation of radial orbit errors with the clock parameters, these errors are also visible as a bump in the Allan deviation of the Galileo satellite clocks at the orbital frequency.

Classification of Satellite Images by means of Fuzzy Rules generated by a Genetic Algorithm

The data acquired by Remote Sensing systems allow obtaining thematic maps of the earth's surface, by means of the registered image classification. This implies the identification and categorization of all pixels into land cover classes. Traditionally, methods based on statistical parameters have been widely used, although they show some disadvantages. Nevertheless, some authors indicate that those methods based on artificial intelligence, may be a good alternative. Thus, fuzzy classifiers, which are based on Fuzzy Logic, include additional information in the classification process through based-rule systems. In this work, we propose the use of a genetic algorithm (GA) to select the optimal and minimum set of fuzzy rules to classify remotely sensed images. Input information of GA has been obtained through the training space determined by two uncorrelated spectral bands (2D scatter diagrams), which has been irregularly divided by five linguistic terms defined in each band. The proposed methodology has been applied to Landsat-TM images and it has showed that this set of rules provides a higher accuracy level in the classification process

Efficient local unfolding with ancestor stacks

The most successful unfolding rules used nowadays in the partial evaluation of logic programs are based on well quasi orders (wqo) applied over (covering) ancestors, i.e., a subsequence of the atoms selected during a derivation. Ancestor (sub)sequences are used to increase the specialization power of unfolding while still guaranteeing termination and also to reduce the number of atoms for which the wqo has to be checked. Unfortunately, maintaining the structure of the ancestor relation during unfolding introduces significant overhead. We propose an efficient, practical local unfolding rule based on the notion of covering ancestors which can be used in combination with a wqo and allows a stack-based implementation without losing any opportunities for specialization. Using our technique, certain non-leftmost unfoldings are allowed as long as local unfolding is performed, i.e., we cover depth-first strategies. To deal with practical programs, we propose assertion-based techniques which allow our approach to treat programs that include (Prolog) built-ins and external predicates in a very extensible manner, for the case of leftmost unfolding. Finally, we report on our mplementation of these techniques embedded in a practical partial evaluator, which shows that our techniques, in addition to dealing with practical programs, are also significantly more efficient in time and somewhat more efficient in memory than traditional tree-based implementations. To appear in Theory and Practice of Logic Programming (TPLP).

Efficient local unfolding with ancestor stacks for full prolog

The integration of powerful partial evaluation methods into practical compilers for logic programs is still far from reality. This is related both to 1) efficiency issues and to 2) the complications of dealing with practical programs. Regarding efnciency, the most successful unfolding rules used nowadays are based on structural orders applied over (covering) ancestors, i.e., a subsequence of the atoms selected during a derivation. Unfortunately, maintaining the structure of the ancestor relation during unfolding introduces significant overhead. We propose an efficient, practical local unfolding rule based on the notion of covering ancestors which can be used in combination with any structural order and allows a stack-based implementation without losing any opportunities for specialization. Regarding the second issue, we propose assertion-based techniques which allow our approach to deal with real programs that include (Prolog) built-ins and external predicates in a very extensible manner. Finally, we report on our implementation of these techniques in a practical partial evaluator, embedded in a state of the art compiler which uses global analysis extensively (the Ciao compiler and, specifically, its preprocessor CiaoPP). The performance analysis of the resulting system shows that our techniques, in addition to dealing with practical programs, are also significantly more efficient in time and somewhat more efficient in memory than traditional tree-based implementations.

A Model of Emotion as Patterned Metacontrol

Adaptive agents use feedback as a key strategy to cope with un- certainty and change in their environments. The information fed back from the sensorimotor loop into the control subsystem can be used to change four different elements of the controller: parameters associated to the control model, the control model itself, the functional organization of the agent and the functional realization of the agent. There are many change alternatives and hence the complexity of the agent’s space of potential configurations is daunting. The only viable alternative for space- and time-constrained agents —in practical, economical, evolutionary terms— is to achieve a reduction of the dimensionality of this configuration space. Emotions play a critical role in this reduction. The reduction is achieved by func- tionalization, interface minimization and by patterning, i.e. by selection among a predefined set of organizational configurations. This analysis lets us state how autonomy emerges from the integration of cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. Emotion-based morphofunctional systems are able to exhibit complex adaptation patterns at a reduced cognitive cost. In this article we show a general model of how emotion supports functional adaptation and how the emotional biological systems operate following this theoretical model. We will also show how this model is also of applicability to the construction of a wide spectrum of artificial systems1.