Growth of phototrophic biofilms from limestone monuments under laboratory conditions

International Biodeterioration & Biodegradation,xxx (2009) 1–8

Tech-based Innovations in pedagogical practices: the case of ISCAP

TICEduca. III Congresso Internacional TIC e Educação. 14 a 16 Novembro, Lisboa

A comprehensive high-throughput FTIR spectroscopy-based method for evaluating the transfection event: estimating the transfection efficiency and extracting associated metabolic responses

Reporter genes are routinely used in every laboratory for molecular and cellular biology for studying heterologous gene expression and general cellular biological mechanisms, such as transfection processes. Although well characterized and broadly implemented, reporter genes present serious limitations, either by involving time-consuming procedures or by presenting possible side effects on the expression of the heterologous gene or even in the general cellular metabolism. Fourier transform mid-infrared (FT-MIR) spectroscopy was evaluated to simultaneously analyze in a rapid (minutes) and high-throughput mode (using 96-wells microplates), the transfection efficiency, and the effect of the transfection process on the host cell biochemical composition and metabolism. Semi-adherent HEK and adherent AGS cell lines, transfected with the plasmid pVAX-GFP using Lipofectamine, were used as model systems. Good partial least squares (PLS) models were built to estimate the transfection efficiency, either considering each cell line independently (R 2 ≥ 0.92; RMSECV ≤ 2 %) or simultaneously considering both cell lines (R 2 = 0.90; RMSECV = 2 %). Additionally, the effect of the transfection process on the HEK cell biochemical and metabolic features could be evaluated directly from the FT-IR spectra. Due to the high sensitivity of the technique, it was also possible to discriminate the effect of the transfection process from the transfection reagent on KEK cells, e.g., by the analysis of spectral biomarkers and biochemical and metabolic features. The present results are far beyond what any reporter gene assay or other specific probe can offer for these purposes.

Immunohistochemical molecular phenotypes of gastric cancer based on SOX2 and CDX2 predict patient outcome

Background Gastric cancer remains a serious health concern worldwide. Patients would greatly benefit from the discovery of new biomarkers that predict outcome more accurately and allow better treatment and follow-up decisions. Here, we used a retrospective, observational study to assess the expression and prognostic value of the transcription factors SOX2 and CDX2 in gastric cancer. Methods SOX2, CDX2, MUC5AC and MUC2 expression were assessed in 201 gastric tumors by immunohistochemistry. SOX2 and CDX2 expression were crossed with clinicopathological and follow-up data to determine their impact on tumor behavior and outcome. Moreover, SOX2 locus copy number status was assessed by FISH (N = 21) and Copy Number Variation Assay (N = 62). Results SOX2 was expressed in 52% of the gastric tumors and was significantly associated with male gender, T stage and N stage. Moreover, SOX2 expression predicted poorer patient survival, and the combination with CDX2 defined two molecular phenotypes, SOX2+CDX2- versus SOX2-CDX2+, that predict the worst and the best long-term patients’ outcome. These profiles combined with clinicopathological parameters stratify the prognosis of patients with intestinal and expanding tumors and in those without signs of venous invasion. Finally, SOX2 locus copy number gains were found in 93% of the samples reaching the amplification threshold in 14% and significantly associating with protein expression. Conclusions We showed, for the first time, that SOX2 combined with CDX2 expression profile in gastric cancer segregate patients into different prognostic groups, complementing the clinicopathological information. We further demonstrate a molecular mechanism for SOX2 expression in a subset of gastric cancer cases.

A PV panel simulator based on a two quadrant DC/DC power converter with a sliding mode controller

The use of a solar photovoltaic (PV) panel simulator can be a valued tool for the design and evaluation of the several components of a photovoltaic system. This simulator is based on power electronic converter controlled in such a way that will behave as a PV panel. Thus, in this paper a PV panel simulator based on a two quadrant DC/DC power converter is proposed. This topology will allow to achieve fast responses, like suddenly changes in the irradiation and temperature. To control the power converter it will be used a fast and robust sliding mode controller. Therefore, with the proposed system I-V curve simulation of a PV panel is obtained. Experimental results from a laboratory prototype are presented in order to confirm the theoretical operation.

Dual-phase inkjet printed electrochromic layers based on PTA and WOX/TiO2 nanoparticles for electrochromic applications

Thesis submitted in Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa for the degree of Master in Materials Engineering

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

COLONIZATION AND LABORATORY MAINTENANCE OFAnopheles albimanus WIEDEMANN IN VENEZUELA

Anopheles albimanus is one of the main vectors of malaria in Central America and the Caribbean, based on its importance, there are previous reports of the successful colonization of this species in Latin America countries. Mosquitoes were collected in the Aragua State of Venezuela colonized in the laboratory, using a simple and efficient maintenance method. Based on life table calculations under well established laboratory conditions, the Survival Rate Probability was constant and always close to 1 in immature stages, the Reproductive Net Rate (Ro) was 3.83, the generation time (Tc) was 24.5 days and the Intrinsic Growth Rate (rm) was 0.0558. This is the first report of the colonization of A. albimanus in Venezuela.

Using children’s literature in ELT: A story-based approach

There has been a growing interest in the role of children’s literature in language teaching since the 80s, when the communicative approach made it possible to bring stories into the classroom (Garvie, 1990). It is undeniable that storytelling has many benefits. Not only are children naturally drawn to stories, but they are also an effective and enjoyable way to teach and learn. This article presents the findings of a MA project on using stories with children. It shows the importance of stories on language acquisition and concludes with some practical suggestions based on my teaching experience with young learners.

hsp65 PCR-restriction enzyme analysis (PRA) for identification of mycobacteria in the clinical laboratory

More than 70 species of mycobacteria have been defined, and some can cause disease in humans, especially in immunocompromised patients. Species identification in most clinical laboratories is based on phenotypic characteristics and biochemical tests and final results are obtained only after two to four weeks. Quick identification methods, by reducing time for diagnosis, could expedite institution of specific treatment, increasing chances of success. PCR restriction-enzyme analysis (PRA) of the hsp65 gene was used as a rapid method for identification of 103 clinical isolates. Band patterns were interpreted by comparison with published tables and patterns available at an Internet site (http://www.hospvd.ch:8005). Concordant results of PRA and biochemical identification were obtained in 76 out of 83 isolates (91.5%). Results from 20 isolates could not be compared due to inconclusive PRA or biochemical identification. The results of this work showed that PRA could improve identification of mycobacteria in a routine setting because it is accurate, fast, and cheaper than conventional phenotypic identification.

PCR - based diagnosis to evaluate the performance of malaria reference centers

Although the Giemsa-stained thick blood smear (GTS) remains the gold standard for the diagnosis of malaria, molecular methods are more sensitive and specific to detect parasites and can be used at reference centers to evaluate the performance of microscopy. The description of the Plasmodium falciparum, P. vivax, P. malariae and P. ovale ssrRNA gene sequences allowed the development of a polymerase chain reaction (PCR) that had been used to differentiate the four species. The objective of this study was to determine Plasmodium species through PCR in 190 positive smears from patients in order to verify the quality of diagnosis at SUCEN's Malaria Laboratory. Considering only the 131 positive results in both techniques, GTS detected 4.6% of mixed and 3.1% of P. malariae infections whereas PCR identified 19.1% and 13.8%, respectively.

Teaching accounting and management through business simulation

Everyday accounting and management teachers face the challenge of creating learning environments that motivate students. This chapter describes the Business Simulation (BS) experience that has taken place at the Polytechnic Institute of Porto, Institute of Accounting and Administration (IPP/ISCAP). The chapter presents students’ perceptions about the course and the teaching/learning approach. The results show that pedagogical methods used (competency-oriented), generic competencies (cooperation and group work), and interpersonal skills (organisational and communication skills) are relevant for future accounting professionals. In addition, positive remarks and possible constraints based on observation, staff meetings, and past research are reported. The chapter concludes with some recommendations from the project implementation

PCR-based identification of Burkholderia pseudomallei

DNA amplification techniques are being used increasingly in clinical laboratories to confirm the identity of medically important bacteria. A PCR-based identification method has been in use in our centre for 10 years for Burkholderia pseudomallei and was used to confirm the identity of bacteria isolated from cases of melioidosis in Ceará since 2003. This particular method has been used as a reference standard for less discriminatory methods. In this study we evaluated three PCR-based methods of B. pseudomallei identification and used DNA sequencing to resolve discrepancies between PCR-based results and phenotypic identification methods. The established semi-nested PCR protocol for B. pseudomallei 16-23s spacer region produced a consistent negative result for one of our 100 test isolates (BCC #99), but correctly identified all 71 other B. pseudomallei isolates tested. Anomalous sequence variation was detected at the inner, reverse primer binding site for this method. PCR methods were developed for detection of two other B. pseudomallei bacterial metabolic genes. The conventional lpxO PCR protocol had a sensitivity of 0.89 and a specificity of 1.00, while a real-time lpxO protocol performed even better with sensitivity and specificity of 1.00, and 1.00. This method identified all B. pseudomallei isolates including the PCR-negative discrepant isolate. The phaC PCR protocol detected the gene in all B. pseudomallei and all but three B. cepacia isolates, making this method unsuitable for PCR-based identification of B. pseudomallei. This experience with PCR-based B. pseudomallei identification methods indicates that single PCR targets should be used with caution for identification of these bacteria, and need to be interpreted alongside phenotypic and alternative molecular methods such as gene sequencing.

Candida bloodstream infection: data from a teaching hospital in Mato Grosso do Sul, Brazil

The incidence of Candida bloodstream infection has increased over the past years. In the Center-West region of Brazil, data on candidemia are scarce. This paper reports a retrospective analysis of 96 cases of Candida bloodstream infection at a Brazilian tertiary-care teaching hospital in the state of Mato Grosso do Sul, from January 1998 to December 2006. Demographic, clinical and laboratory data were collected from medical records and from the hospital's laboratory database. Patients' ages ranged from three days to 92 years, with 53 (55.2%) adults and 43 (44.8%) children. Of the latter, 25 (58.1%) were newborns. The risk conditions most often found were: long period of hospitalization, utilization of venous central catheter, and previous use of antibiotics. Fifty-eight (60.4%) patients died during the hospitalization period and eight (13.7%) of them died 30 days after the diagnosis of candidemia. Candida albicans (45.8%) was the most prevalent species, followed by C. parapsilosis (34.4%), C. tropicalis (14.6%) and C. glabrata (5.2%). This is the first report of Candida bloodstream infection in the state of Mato Grosso do Sul and it highlights the importance of considering the possibility of invasive Candida infection in patients exposed to risk factors, particularly among neonates and the elderly.

A rule-based grapheme-to-phone converter for TTS systems in european portuguese

In this paper, a linguistically rule-based grapheme-to-phone (G2P) transcription algorithm is described for European Portuguese. A complete set of phonological and phonetic transcription rules regarding the European Portuguese standard variety is presented. This algorithm was implemented and tested by using online newspaper articles. The obtained experimental results gave rise to 98.80% of accuracy rate. Future developments in order to increase this value are foreseen. Our purpose with this work is to develop a module/ tool that can improve synthetic speech naturalness in European Portuguese. Other applications of this system can be expected like language teaching/learning. These results, together with our perspectives of future improvements, have proved the dramatic importance of linguistic knowledge on the development of Text-to-Speech systems (TTS).