Cross-Over between Discrete and Continuous Protein Structure Space: Insights into Automatic Classification and Networks of Protein Structures

Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we have selected a consensus set of 2,890 domains decomposed very similarly in SCOP and CATH. As an alignment algorithm, we used a global version of MAMMOTH developed in our group, which is both rapid and accurate. As a similarity measure, we used the size-normalized contact overlap, and as a clustering algorithm, we used average linkage. The resulting automatic classification at the cross-over point was more consistent than expert ones with respect to the structure similarity measure, with 86% of the clusters corresponding to subsets of either SCOP or CATH superfamilies and fewer than 5% containing domains in distinct folds according to both SCOP and CATH. Almost 15% of SCOP superfamilies and 10% of CATH superfamilies were split, consistent with the notion of fold change in protein evolution. These results were qualitatively robust for all choices that we tested, although we did not try to use alignment algorithms developed by other groups. Folds defined in SCOP and CATH would be completely joined in the regime of large transitivity violations where clustering is more arbitrary. Consistently, the agreement between SCOP and CATH at fold level was lower than their agreement with the automatic classification obtained using as a clustering algorithm, respectively, average linkage (for SCOP) or single linkage (for CATH). The networks representing significant evolutionary and structural relationships between clusters beyond the cross-over point may allow us to perform evolutionary, structural, or functional analyses beyond the limits of classification schemes. These networks and the underlying clusters are available at http://ub.cbm.uam.es/research/ProtNet.ph

Overview of cattle diseases listed under category C, D or E in the animal health law for wich control programmes are in place within Europe

13 páginas, 5 figuras, 3 tablas.The COST action “Standardising output-based surveillance to control non-regulated diseases of cattle in the European Union (SOUND control),” aims to harmonise the results of surveillance and control programmes (CPs) for non-EU regulated cattle diseases to facilitate safe trade and improve overall control of cattle infectious diseases. In this paper we aimed to provide an overview on the diversity of control for these diseases in Europe. A non-EU regulated cattle disease was defined as an infectious disease of cattle with no or limited control at EU level, which is not included in the European Union Animal health law Categories A or B under Commission Implementing Regulation (EU) 2020/2002. A CP was defined as surveillance and/or intervention strategies designed to lower the incidence, prevalence, mortality or prove freedom from a specific disease in a region or country. Passive surveillance, and active surveillance of breeding bulls under Council Directive 88/407/EEC were not considered as CPs. A questionnaire was designed to obtain country-specific information about CPs for each disease. Animal health experts from 33 European countries completed the questionnaire. Overall, there are 23 diseases for which a CP exists in one or more of the countries studied. The diseases for which CPs exist in the highest number of countries are enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis, bovine viral diarrhoea and anthrax (CPs reported by between 16 and 31 countries). Every participating country has on average, 6 CPs (min–max: 1–13) in place. Most programmes are implemented at a national level (86%) and are applied to both dairy and non-dairy cattle (75%). Approximately one-third of the CPs are voluntary, and the funding structure is divided between government and private resources. Countries that have eradicated diseases like enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis and bovine viral diarrhoea have implemented CPs for other diseases to further improve the health status of cattle in their country. The control of non-EU regulated cattle diseases is very heterogenous in Europe. Therefore, the standardising of the outputs of these programmes to enable comparison represents a challenge.Peer reviewe

Analysis of use of satellite imagery for extraction of snow cover distribution as a parameter in a rainfall-runoff model

Analysis of use of satellite imagery for extraction of snow cover distribution as a parameter in a rainfall-runoff model.Interpolation of point measurements of meteorological variables in relatively big areas (eg. medium and big catchments) does not refl ect their real distribution. The study area is the upper Biebrza River catchment, meteorological data were recorded in a Rogorzynek station. This paper analyses possibilities of usage of a satellite data (MOD10A2, a spatial distribution of a snow cover) as a parameter in a hydrological model, which uses a day-degree method for a snowmelt estimation. The analysis shown a high correlation (0.68) between presence of a snow cover in a land surface station and in satellite data. Moreover, a strong linear relationship (correlation of 0.70) was found between a snow pack depth in the land surface station and an area of snow cover in the catchment estimated from satellite data. Geostatistical analysis of snow cover frequency in a pixel was made. A method of use a MOD10A2 data in a hydrological model was proposed.Interpolacja mierzonych punktowo zjawisk meteorologicznych dla relatywnie dużych obszarów (np. średnich i dużych zlewni) nie oddaje ich rzeczywistego rozkładu. Terenem badań jest zlewnia górnej Biebrzy po profil Sztabin, dane meteorologiczne pochodzą ze stacji Rogożynek. Artykuł ten przedstawia możliwość wykorzystania danych satelitarnych MOD10A2 przedstawiających przestrzenne rozłożenie pokrywy śnieżnej, jako parametru w modelu hydrologicznym szacującym roztopy śniegu metodą stopień-dzień. Przeprowadzona analiza wykazała wysoką korelację (0,68) między pomiarami obecności pokrywy śnieżnej w stacji meteorologicznej a pomiarami satelitarnymi. Ponadto wykazano silny związek liniowy (korelacja równa 0,70) między grubością pokrywy śnieżnej mierzonej w stacji meteorologicznej, a obszarem pokrywy śnieżnej w zlewni mierzonej za pomocą satelity. Zaproponowano możliwość włączenia danych MOD10A2 do obliczeń modelu hydrologicznego

Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model

As the availability of spatially distributed data sets for distributed rainfall-runoff modelling is strongly increasing, more attention should be paid to the influence of the quality of the data on the calibration. While a lot of progress has been made on using distributed data in simulations of hydrological models, sensitivity of spatial data with respect to model results is not well understood. In this paper we develop a spatial sensitivity analysis method for spatial input data (snow cover fraction – SCF) for a distributed rainfall-runoff model to investigate when the model is differently subjected to SCF uncertainty in different zones of the model. The analysis was focussed on the relation between the SCF sensitivity and the physical and spatial parameters and processes of a distributed rainfall-runoff model. The methodology is tested for the Biebrza River catchment, Poland, for which a distributed WetSpa model is set up to simulate 2 years of daily runoff. The sensitivity analysis uses the Latin-Hypercube One-factor-At-a-Time (LH-OAT) algorithm, which employs different response functions for each spatial parameter representing a 4 × 4 km snow zone. The results show that the spatial patterns of sensitivity can be easily interpreted by co-occurrence of different environmental factors such as geomorphology, soil texture, land use, precipitation and temperature. Moreover, the spatial pattern of sensitivity under different response functions is related to different spatial parameters and physical processes. The results clearly show that the LH-OAT algorithm is suitable for our spatial sensitivity analysis approach and that the SCF is spatially sensitive in the WetSpa model. The developed method can be easily applied to other models and other spatial data

Impact of remotely sensed land-cover proportions on urban runoff prediction

Land-cover impacts volume, intensity and contamination of runoff generated by rainfall events in catchments. This study demonstrates how the method used for estimation of land-cover proportions impacts the runoff from a distributed, physically based hydrological model-WetSpa. The study area is the urbanized catchment of Biala River, situated in the northeastern part of Poland. Three scenarios of landcover proportion estimation were tested: a semi-distributed approach where the average proportion of impervious surface cover per land-use type is estimated based on hard classification of a high-resolution IKONOS scene and two distributed approaches with land-cover class proportions estimated at the level of individual cells based on hard classification of a high-resolution IKONOS scene and sub-pixel classification of a medium-resolution Landsat 5 TM scene respectively. Validation of the three scenarios based on a comparison of modeled versus observed discharge shows that best results are obtained for the two distributed scenarios with a Nash-Sutcliffe efficiency (NS) of 0.62 for the hard classification approach and NS = 0.63 for the sub-pixel approach. The hard classification approach performed best in the estimation of peak discharges. The semi-distributed modeling scenario resulted in the lowest simulation efficiency (NS = 0.40) and did not perform well in estimating observed peak discharges. It is concluded that scenarios in which land-cover proportions are distributed improved considerably the simulation results of hydrological processes in physically based models. © 2011 Elsevier B.V.status: publishe

CPLFD-GDPT5: High-resolution gridded daily precipitation and temperature data set for two largest Polish river basins

The CHASE-PL (Climate change impact assessment for selected sectors in Poland) Forcing Data–Gridded Daily Precipitation &amp; Temperature Dataset–5 km (CPLFD-GDPT5) consists of 1951–2013 daily minimum and maximum air temperatures and precipitation totals interpolated onto a 5 km grid based on daily meteorological observations from the Institute of Meteorology and Water Management (IMGW-PIB; Polish stations), Deutscher Wetterdienst (DWD, German and Czech stations), and European Climate Assessment and Dataset (ECAD) and National Oceanic and Atmosphere Administration–National Climatic Data Center (NOAA-NCDC) (Slovak, Ukrainian, and Belarusian stations). The main purpose for constructing this product was the need for long-term aerial precipitation and temperature data for earth-system modelling, especially hydrological modelling. The spatial coverage is the union of the Vistula and Oder basins and Polish territory. The number of available meteorological stations for precipitation and temperature varies in time from about 100 for temperature and 300 for precipitation in the 1950s up to about 180 for temperature and 700 for precipitation in the 1990s. The precipitation data set was corrected for snowfall and rainfall under-catch with the Richter method. The interpolation methods were kriging with elevation as external drift for temperatures and indicator kriging combined with universal kriging for precipitation. The kriging cross validation revealed low root-mean-squared errors expressed as a fraction of standard deviation (SD): 0.54 and 0.47 for minimum and maximum temperature, respectively, and 0.79 for precipitation. The correlation scores were 0.84 for minimum temperatures, 0.88 for maximum temperatures, and 0.65 for precipitation. The CPLFD-GDPT5 product is consistent with 1971–2000 climatic data published by IMGW-PIB. We also confirm good skill of the product for hydrological modelling by performing an application using the Soil and Water Assessment Tool (SWAT) in the Vistula and Oder basins.<br><br> Link to the data set: <a href="http://dx.doi.org/10.4121/uuid:e939aec0-bdd1-440f-bd1e-c49ff10d0a07" target="_blank">doi:10.4121/uuid:e939aec0-bdd1-440f-bd1e-c49ff10d0a07</a>

LONGITUDINAL REFERENCE VALUES FOR DUCTUS VENOSUS DOPPLER IN LOW-RISK PREGNANCIES

The aim of this study was to establish normal ranges of blood flow velocities and indices in the fetal ductus venosus (DV) during the second half of normal pregnancy. A Doppler study of 60 healthy pregnant women without fetal pathologies was performed during the second half of pregnancy. The peak systolic velocity (PSV), peak diastolic velocity (PDV), maximum velocity during atrial contraction (VAC), peak systolic velocity/maximum velocity during atrial contraction (S/A ratio), pulsatility index for the vein (PIV), preload index (PLI) and velocity index for the vein (VIV) were calculated from the DV at 4-week intervals. A significant increase in PSV, PDV and VAC was observed from the 20-23(6/7) to the 28-31(6/7) weeks, with stabilization of values until the end of the pregnancy. On the other hand, the study showed a significant decrease for the S/A ratio, PIV, PLI and VIV from the 20-23(6/7) to the 28-31(6/7) weeks and remaining stable from then until term. (E-mail:[email protected]) (C) 2010 World Federation for Ultrasound in Medicine & Biology.FAPES