Early detection of severe sepsis in the emergency room in adults - Clinical utility of prognostic markers

Vaikean sepsiksen varhainen tunnistaminen päivystyspoliklinikalla – merkkiaineiden käyttökelpoisuus aikuispotilaiden arvioinnissa Päivystyspotilaan vakavan yleisinfektion eli sepsiksen varhainen tunnistaminen ja taudin vaikeusasteen arviointi on päivystävälle lääkärille tärkeä haaste. Arvioimme prospektiivisessa kohorttitutkimuksessa eri merkkiaineiden hyödyllisyyttä sepsiksen varhaisessa tunnistamisessa ja vaikeusasteen arvioinnissa. Työssä I ja III oli 539 päivystyspotilasta, joilta kliinikko päätti ottaa veriviljelyn sepsistä epäillen. Tutkimuksessa II oli 525 potilasta ja tutkimuksessa IV 537 potilasta. Tutkimuksessa I plasman C-reaktiivisen proteiinin (CRP) pitoisuuksia verrattiin plasman prokalsitoniinin (PCT) ja interleukiinin (IL-6) pitoisuuksiin. Tutkimuksessa II verrattiin plasman baktersidisen/ permeabiliteettia lisäävän proteiinin (BPI), ryhmän IIA fosfolipaasi A2:n (PLA2GIIA) ja CRP:n pitoisuuksia sekä valkosolujen määriä toisiinsa. Tutkimuksessa III arvioitiin liukoisen urokinaasi-tyyppisen plasminogeenin aktivaattorireseptorin (suPAR) ja tutkimuksessa IV pentraksiini 3:n (PTX3) määrityksen käyttökelpoisuutta. Tutkimuksessa I todettiin päivystystilanteessa mitattujen korkeiden PCT - ja IL-6 - pitoisuuksien ennustavan vaikean sepsiksen kehittymistä paremmin kuin korkean CRP:n. Tutkimuksessa II plasman PLA2GIIA vaikutti hiukan paremmalta vaikean sepsiksen ennustajalta kuin CRP tai veren valkosolutaso, mutta BPI ei ollut hyödyllinen. Tutkimuksessa III korkea plasman suPAR- pitoisuus osoittautui itsenäiseksi kuolleisuuden riskitekijäksi ja se liittyi myös vaikean sepsiksen kehittymiseen. Tutkimuksessa IV korkea PTX3 - pitoisuus toimi samaan tapaan kuin suPAR. Kokonaisuutena PCT osoittautui parhaaksi merkkiaineeksi ennustamaan elinhäiriön kehittymistä ja suPAR kuolleisuutta. PTX3 ei tarjonnut merkittävää lisäetua PCT:iin ja suPAR:iin verrattuna. CRP osoitti suhteellisen hyvin bakteeri-infektion esiintymistä, mutta ennusteellista arvoa sillä ei ollut. suPAR on kiinnostava kuolleisuuden ja elinhäiriön kehittymisen merkkiaine.

Phenology, fruit set and dispersal of Cordia multispicata Cham., an important weed shrub of abandoned pastures in eastern Amazonia

ABSTRACT - (Phenology, fruit set and dispersal of Cordia multispicata Cham., an important weed shrub of abandoned pastures in eastern Amazonia). The reproductive ecology of the distylous tropical shrub Cordia multispicata was studied in an abandoned pasture in Paragominas County , Pará state, Brazil. It is a common species in the Amazon basin where it occurs as a weed in open and disturbed habitats. C. multispicata has many flowers per inflorescence (85 ± 12) but 84% abort before fertilization. Flowering occurs throughout the year. Fruits are small, with a red fleshy pericarp (skin-pulp) attractive to birds. Fruit set is lower during the dry season (less than 30%) and higher during the rainy season when there are many visits of insects to the flowers. Fruiting has a peak between the end of the dry season and the middle of the rainy season. Nineteen bird species were observed foraging for the fruits of C. multispicata, and 79% of those species can be considered as potential dispersal agents. The efficient seed dispersal and aggregated spatial distribution associated with some characteristics of the dispersors greatly contributed to the success of this species in abandoned pastures of eastern Amazonia.

Packaging Content for Aggregated and Federated Repositories through APTrust

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Flowering phenology, seed set and arthropod guilds in Trichogoniopsis adenantha (DC) (Asteraceae) in south-east Brazil

and glades. This species blooms throughout the year, attracting arthropods of various guilds, including herbivores, pollinators and predators. In this study, done over a two year period, we described the phenology of T. adenantha and assessed the seasonal variation in arthropod numbers of different guilds. We also determined the periods of lowest and highest seed set. T. adenantha population showed a peak in flowering in March-April (rainy season) with greater production of achenes in December-April. April and October had respectively highest and lowest number of fertilized, undamaged ovules, and this pattern is possibly related with population dynamics of pollinators and herbivores. In August, which was the period of greatest damage to the stigma (by geometrid larvae), there was a positive relationship between the proportion of unfertilized ovules and flowers with damaged stigma, suggesting that floral herbivory may affect reproduction in T. adenantha. We discuss the complex dynamics of the beneficial and harmful interactions between arthropods and the host plant.

Pollination and fruit set in pumpkin (Cucurbita pepo) by honey bees

Species of Cucurbitaceae are cultivated worldwide and are depend on bee pollination for fruit set. Field and lab experiments were conducted at Cornell University, Ithaca, NY, during 1996 and 1997 to determine "Howden" pumpkin (Cucurbita pepo L.) pollen removal and deposition by honeybees and factors relating to male flower attractiveness. Several parameters were evaluated in flowers at anthesis: (1) removal of pollen from anthers by honey bees, (2) pollen deposition on the stigma by honey bees, (3) amount of pollen on the body of honey bees, (4) fruit set after bee pollination, and (5) male flower nectary's pores and flower attractiveness. Honey bees carried between 1,050 to 3,990 pollen grains and 13,765 were removed from an anther after one visit. The amount of pollen deposited on the stigma by the honey bees varied according to the number of visits, from 53 grains with one visit, to 1,253 grains with 12 visits, and the mean number of grains in each visit varied from 53 to 230 grains. The percentage of established fruits was higher (100%) when the flowers received 12 visits of Apis mellifera, corresponding to a load 1,253 pollen grains. The attractiveness of the male flower for pollen and nectar collection was increased by the degree of opening of the access pore to the nectary in the flower.

The use of protein structure/activity relationships in the rational design of stable particulate delivery systems

The recombinant heat shock protein (18 kDa-hsp) from Mycobacterium leprae was studied as a T-epitope model for vaccine development. We present a structural analysis of the stability of recombinant 18 kDa-hsp during different processing steps. Circular dichroism and ELISA were used to monitor protein structure after thermal stress, lyophilization and chemical modification. We observed that the 18 kDa-hsp is extremely resistant to a wide range of temperatures (60% of activity is retained at 80ºC for 20 min). N-Acylation increased its ordered structure by 4% and decreased its ß-T1 structure by 2%. ELISA demonstrated that the native conformation of the 18 kDa-hsp was preserved after hydrophobic modification by acylation. The recombinant 18 kDa-hsp resists to a wide range of temperatures and chemical modifications without loss of its main characteristic, which is to be a source of T epitopes. This resistance is probably directly related to its lack of organization at the level of tertiary and secondary structures.

Reliability and clinical utility of a Portuguese version of the Abnormal Involuntary Movements Scale (AIMS) for tardive dyskinesia in Brazilian patients

The objective of the present study was to evaluate the reliability and clinical utility of a Portuguese version of the Abnormal Involuntary Movements Scale (AIMS). Videotaped interviews with 16 psychiatric inpatients treated with antipsychotic drugs for at least 5 years were evaluated. Reliability was assessed by the intraclass correlation coefficient (ICC) between three raters, two with and one without clinical training in psychopathology. Clinical utility was assessed by the difference between the scores of patients with (N = 11) and without (N = 5) tardive dyskinesia (TD). Patients with TD exhibited a higher severity of global evaluation by the AIMS (sum of scores: 4.2 ± 0.9 vs 0.4 ± 0.2; score on item 8: 2.3 ± 0.3 vs 0.4 ± 0.2, TD vs controls). The ICC for the global evaluation was fair between the two skilled raters (0.58-0.62) and poor between these raters and the rater without clinical experience (0.05-0.29). Thus, we concluded that the Portuguese version of the AIMS shows an acceptable inter-rater reliability, but only between clinically skilled raters, and that it is clinically useful.

Pinoamislaitteen suunnittelu vetokoneen jälkeiselle linjalle

Työn tavoitteena oli suunnitella vetokoneen linjalle pinoamislaite. Laitteen tehtävänä on pinota yksittäin vetokoneelta tulevista tuotteista asiakasvaatimusten mukaisia pinoja. Laitteen suunnittelu toteutettiin käyttämällä systemaattisen koneensuunnittelun metodia. Diplomityö rajattiin koskemaan laitteen mekaanisten ratkaisujen suunnittelua. Suunnittelussa huomioitiin linjan asettamat vaatimukset, jotka koskevat sekä tuotantomäärää että tilojen käyttöä. Laitteen suunnittelussa ja mallinnuksessa käytettiin Solidworksin 3D-mallinnusohjelmaa. Mallinnettuja ratkaisuvaihtoehtoja verrattiin keskenään. Parhaiten vaatimusluettelossa esitetyt vaatimukset täyttänyt ratkaisumalli valittiin kehitettäväksi. Suunnitellusta laitteesta valmistettiin työpiirustukset sekä kokoonpanokuvat.

Analyzing the Effects of the New Renewable Energy Policy in Russia on Investments into Wind, Solar and Small Hydro Power

This thesis presents an analysis of recently enacted Russian renewable energy policy based on capacity mechanism. Considering its novelty and poor coverage by academic literature, the aim of the thesis is to analyze capacity mechanism influence on investors’ decision-making process. The current research introduces a number of approaches to investment analysis. Firstly, classical financial model was built with Microsoft Excel® and crisp efficiency indicators such as net present value were determined. Secondly, sensitivity analysis was performed to understand different factors influence on project profitability. Thirdly, Datar-Mathews method was applied that by means of Monte Carlo simulation realized with Matlab Simulink®, disclosed all possible outcomes of investment project and enabled real option thinking. Fourthly, previous analysis was duplicated by fuzzy pay-off method with Microsoft Excel®. Finally, decision-making process under capacity mechanism was illustrated with decision tree. Capacity remuneration paid within 15 years is calculated individually for each RE project as variable annuity that guarantees a particular return on investment adjusted on changes in national interest rates. Analysis results indicate that capacity mechanism creates a real option to invest in renewable energy project by ensuring project profitability regardless of market conditions if project-internal factors are managed properly. The latter includes keeping capital expenditures within set limits, production performance higher than 75% of target indicators, and fulfilling localization requirement, implying producing equipment and services within the country. Occurrence of real option shapes decision-making process in the following way. Initially, investor should define appropriate location for a planned power plant where high production performance can be achieved, and lock in this location in case of competition. After, investor should wait until capital cost limit and localization requirement can be met, after that decision to invest can be made without any risk to project profitability. With respect to technology kind, investment into solar PV power plant is more attractive than into wind or small hydro power, since it has higher weighted net present value and lower standard deviation. However, it does not change decision-making strategy that remains the same for each technology type. Fuzzy pay-method proved its ability to disclose the same patterns of information as Monte Carlo simulation. Being effective in investment analysis under uncertainty and easy in use, it can be recommended as sufficient analytical tool to investors and researchers. Apart from described results, this thesis contributes to the academic literature by detailed description of capacity price calculation for renewable energy that was not available in English before. With respect to methodology novelty, such advanced approaches as Datar-Mathews method and fuzzy pay-off method are applied on the top of investment profitability model that incorporates capacity remuneration calculation as well. Comparison of effects of two different RE supporting schemes, namely Russian capacity mechanism and feed-in premium, contributes to policy comparative studies and exhibits useful inferences for researchers and policymakers. Limitations of this research are simplification of assumptions to country-average level that restricts our ability to analyze renewable energy investment region wise and existing limitation of the studying policy to the wholesale power market that leaves retail markets and remote areas without our attention, taking away medium and small investment into renewable energy from the research focus. Elimination of these limitations would allow creating the full picture of Russian renewable energy investment profile.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Clinical utility of standard base excess in the diagnosis and interpretation of metabolic acidosis in critically ill patients

The aims of this study were to determine whether standard base excess (SBE) is a useful diagnostic tool for metabolic acidosis, whether metabolic acidosis is clinically relevant in daily evaluation of critically ill patients, and to identify the most robust acid-base determinants of SBE. Thirty-one critically ill patients were enrolled. Arterial blood samples were drawn at admission and 24 h later. SBE, as calculated by Van Slyke's (SBE VS) or Wooten's (SBE W) equations, accurately diagnosed metabolic acidosis (AUC = 0.867, 95%CI = 0.690-1.043 and AUC = 0.817, 95%CI = 0.634-0.999, respectively). SBE VS was weakly correlated with total SOFA (r = -0.454, P < 0.001) and was similar to SBE W (r = -0.482, P < 0.001). All acid-base variables were categorized as SBE VS <-2 mEq/L or SBE VS <-5 mEq/L. SBE VS <-2 mEq/L was better able to identify strong ion gap acidosis than SBE VS <-5 mEq/L; there were no significant differences regarding other variables. To demonstrate unmeasured anions, anion gap (AG) corrected for albumin (AG A) was superior to AG corrected for albumin and phosphate (AG A+P) when strong ion gap was used as the standard method. Mathematical modeling showed that albumin level, apparent strong ion difference, AG A, and lactate concentration explained SBE VS variations with an R² = 0.954. SBE VS with a cut-off value of <-2 mEq/L was the best tool to diagnose clinically relevant metabolic acidosis. To analyze the components of SBE VS shifts at the bedside, AG A, apparent strong ion difference, albumin level, and lactate concentration are easily measurable variables that best represent the partitioning of acid-base derangements.

Gene trio signatures as molecular markers to predict response to doxorubicin cyclophosphamide neoadjuvant chemotherapy in breast cancerpatients

In breast cancer patients submitted to neoadjuvant chemotherapy (4 cycles of doxorubicin and cyclophosphamide, AC), expression of groups of three genes (gene trio signatures) could distinguish responsive from non-responsive tumors, as demonstrated by cDNA microarray profiling in a previous study by our group. In the current study, we determined if the expression of the same genes would retain the predictive strength, when analyzed by a more accessible technique (real-time RT-PCR). We evaluated 28 samples already analyzed by cDNA microarray, as a technical validation procedure, and 14 tumors, as an independent biological validation set. All patients received neoadjuvant chemotherapy (4 AC). Among five trio combinations previously identified, defined by nine genes individually investigated (BZRP, CLPTM1,MTSS1, NOTCH1, NUP210, PRSS11, RPL37A, SMYD2, and XLHSRF-1), the most accurate were established by RPL37A, XLHSRF-1based trios, with NOTCH1 or NUP210. Both trios correctly separated 86% of tumors (87% sensitivity and 80% specificity for predicting response), according to their response to chemotherapy (82% in a leave-one-out cross-validation method). Using the pre-established features obtained by linear discriminant analysis, 71% samples from the biological validation set were also correctly classified by both trios (72% sensitivity; 66% specificity). Furthermore, we explored other gene combinations to achieve a higher accuracy in the technical validation group (as a training set). A new trio, MTSS1, RPL37 and SMYD2, correctly classified 93% of samples from the technical validation group (95% sensitivity and 80% specificity; 86% accuracy by the cross-validation method) and 79% from the biological validation group (72% sensitivity and 100% specificity). Therefore, the combined expression of MTSS1, RPL37 and SMYD2, as evaluated by real-time RT-PCR, is a potential candidate to predict response to neoadjuvant doxorubicin and cyclophosphamide in breast cancer patients.