Avanços recentes em biologia celular e molecular, questões éticas implicadas e sua abordagem em aulas de biologia no ensino médio: um estudo de caso

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Influence of Fixation Products Used in the Histological Processing in the FTIR Spectra of Lung Cells

The aim of the present study is to evaluate the differences on FTIR spectra of the normal lung cell (noncancerous mice lung epithelial cell line e10) due to different fixation protocols for histological processing. The results shown that formalin and methacarn (normally used in fixation) did cause many changes on the FTIR spectra of mice lung cells e10, mainly in the organic compounds (800-1800 cm(-1)) in lipids, DNA, and proteins, and the alcohol 70% fixation protocol caused almost no changes on the FTIR spectra compared to unfixed cells spectra (in PBS). It can be concluded that histological processing with alcohol 70% fixation protocol can be used in the FTIR study of mice lung cell line e10.

Genomic analysis of ERVWE2 locus in patients with multiple sclerosis: absence of genetic association but potential role of human endogenous retrovirus type W elements in molecular mimicry with myelin antigen

Human endogenous retroviruses (HERVs) arise from ancient infections of the host germline cells by exogenous retroviruses, constituting 8% of the human genome. Elevated level of envelope transcripts from HERVs-W has been detected in CSF, plasma and brain tissues from patients with Multiple Sclerosis (MS), most of them from Xq22.3, 15q21.3, and 6q21 chromosomes. However, since the locus Xq22.3 (ERVWE2) lack the 5' LTR promoter and the putative protein should be truncated due to a stop codon, we investigated the ERVWE2 genomic loci from 84 individuals, including MS patients with active HERV-W expression detected in PBMC. In addition, an automated search for promoter sequences in 20 kb nearby region of ERVWE2 reference sequence was performed. Several putative binding sites for cellular cofactors and enhancers were found, suggesting that transcription may occur via alternative promoters. However, ERVWE2 DNA sequencing of MS and healthy individuals revealed that all of them harbor a stop codon at site 39, undermining the expression of a full-length protein. Finally, since plaque formation in central nervous system (CNS) of MS patients is attributed to immunological mechanisms triggered by autoimmune attack against myelin, we also investigated the level of similarity between envelope protein and myelin oligodendrocyte glycoprotein (MOG). Comparison of the MOG to the envelope identified five retroviral regions similar to the Ig-like domain of MOG. Interestingly, one of them includes T and B cell epitopes, capable to induce T effector functions and circulating Abs in rats. In sum, although no DNA substitutions that would link ERVWE2 to the MS pathogeny was found, the similarity between the envelope protein to MOG extends the idea that ERVEW2 may be involved on the immunopathogenesis of MS, maybe facilitating the MOG recognizing by the immune system. Although awaiting experimental evidences, the data presented here may expand the scope of the endogenous retroviruses involvement on MS pathogenesis

Image analysis in the morphological and morphometric study of teeth

The subject of this doctoral dissertation concerns the definition of a new methodology for the morphological and morphometric study of fossilized human teeth, and therefore strives to provide a contribution to the reconstruction of human evolutionary history that proposes to extend to the different species of hominid fossils. Standardized investigative methodologies are lacking both regarding the orientation of teeth subject to study and in the analysis that can be carried out on these teeth once they are oriented. The opportunity to standardize a primary analysis methodology is furnished by the study of certain early Neanderthal and preneanderthal molars recovered in two caves in southern Italy [Grotta Taddeo (Taddeo Cave) and Grotta del Poggio (Poggio Cave), near Marina di Camerata, Campania]. To these we can add other molars of Neanderthal and modern man of the upper Paleolithic era, specifically scanned in the paleoanthropology laboratory of the University of Arkansas (Fayetteville, Arkansas, USA), in order to increase the paleoanthropological sample data and thereby make the final results of the analyses more significant. The new analysis methodology is rendered as follows: 1. Standardization of an orientation system for primary molars (superior and inferior), starting from a scan of a sample of 30 molars belonging to modern man (15 M1 inferior and 15 M1 superior), the definition of landmarks, the comparison of various systems and the choice of a system of orientation for each of the two dental typologies. 2. The definition of an analysis procedure that considers only the first 4 millimeters of the dental crown starting from the collar: 5 sections parallel to the plane according to which the tooth has been oriented are carried out, spaced 1 millimeter between them. The intention is to determine a method that allows for the differentiation of fossilized species even in the presence of worn teeth. 3. Results and Conclusions. The new approach to the study of teeth provides a considerable quantity of information that can better be evaluated by increasing the fossil sample data. It has been demonstrated to be a valid tool in evolutionary classification that has allowed (us) to differentiate the Neanderthal sample from that of modern man. In a particular sense the molars of Grotta Taddeo, which up until this point it has not been possible to determine with exactness their species of origin, through the present research they are classified as Neanderthal.

CT perfusion image processing: analysis of liver tumors

Perfusion CT imaging of the liver has potential to improve evaluation of tumour angiogenesis. Quantitative parameters can be obtained applying mathematical models to Time Attenuation Curve (TAC). However, there are still some difficulties for an accurate quantification of perfusion parameters due, for example, to algorithms employed, to mathematical model, to patient’s weight and cardiac output and to the acquisition system. In this thesis, new parameters and alternative methodologies about liver perfusion CT are presented in order to investigate the cause of variability of this technique. Firstly analysis were made to assess the variability related to the mathematical model used to compute arterial Blood Flow (BFa) values. Results were obtained implementing algorithms based on “ maximum slope method” and “Dual input one compartment model” . Statistical analysis on simulated data demonstrated that the two methods are not interchangeable. Anyway slope method is always applicable in clinical context. Then variability related to TAC processing in the application of slope method is analyzed. Results compared with manual selection allow to identify the best automatic algorithm to compute BFa. The consistency of a Standardized Perfusion Index (SPV) was evaluated and a simplified calibration procedure was proposed. At the end the quantitative value of perfusion map was analyzed. ROI approach and map approach provide related values of BFa and this means that pixel by pixel algorithm give reliable quantitative results. Also in pixel by pixel approach slope method give better results. In conclusion the development of new automatic algorithms for a consistent computation of BFa and the analysis and definition of simplified technique to compute SPV parameter, represent an improvement in the field of liver perfusion CT analysis.

Structural analysis of a UAV wing through image processing and FEM

Analisi strutturale dell’ala di un UAV (velivolo senza pilota a bordo), sviluppata usando varie metodologie: misurazioni sperimentali statiche e dinamiche, e simulazioni numeriche con l’utilizzo di programmi agli elementi finiti. L’analisi statica è stata a sua volta portata avanti seguendo due differenti metodi: la classica e diretta determinazione degli spostamenti mediante l’utilizzo di un catetometro e un metodo visivo, basato sull’elaborazione di immagini e sviluppato appositamente a tale scopo in ambiente Matlab. Oltre a ciò è stata svolta anche una analisi FEM volta a valutare l’errore che si ottiene affrontando il problema con uno studio numerico. Su tale modello FEM è stata svolta anche una analisi di tipo dinamico con lo scopo di confrontare tali dati con i dati derivanti da un test dinamico sperimentale per ottenere informazioni utili per una seguente possibile analisi aeroelastica.

[Molecular biology of malignant lymphomas for non-specialists]

Lymphomas comprise a variety of entities with remarkable clinical heterogeneity. This review summarizes the current knowledge on the pathogenesis of major mature B-cell lymphoma subtypes for clinicians working outside the field of hemato-oncology. The understanding of the pathogenesis of lymphomas is linked to the knowledge on normal B-cell differentiation. The clinical diversity is manifested in the different mechanisms involved in lymphomagenesis that include characteristic chromosomal translocations deregulating proto-oncogenes, and inactivation of tumor suppressor genes through deletions and mutations. Gene-expression profiling has dissected certain lymphomas into morphologically indistinguishable, but clinically important subgroups and uncovered pathways suitable for specific therapeutic interventions.

RNA interference in mammalian cell systems

In the last decade, few areas of biology have been transformed as thoroughly as RNA molecular biology. Without any doubt, one of the most significant advances has been the discovery of small (20-30 nucleotide) noncoding RNAs that regulate genes and genomes. The effects of small RNAs on gene expression and control are generally inhibitory, and the corresponding regulatory mechanisms are therefore collectively subsumed under the heading of RNA silencing and/or RNA interference. Two primary categories of these small RNAs - short interfering RNAs (siRNAs) and microRNAs (miRNAs) - act in both somatic and germline lineages of eukaryotic species to regulate endogenous genes and to defend the genome from invasive nucleic acids. Recent advances have revealed unexpected diversity in their biogenesis pathways and the regulatory mechanisms that they access. Our understanding of siRNA and miRNA-based regulation has direct implications for fundamental biology as well as disease aetiology and treatment as it is discussed in this review on 'new techniques in molecular biology'.

The use of light- and electron microscopy for studies on the cell- and molecular biology of parasites and parasitic diseases

Lightmicroscopical (LM) and electron microscopi cal (EM) techniques, have had a major influence on the development and direction of cell biology, and particularly also on the investigation of complex host-parasite relationships. Earlier, microscopy has been rather descriptive, but new technical and scientific advances have changed the situation. Microscopy has now become analytical, quantitative and three-dimensional, with greater emphasis on analysis of live cells with fluorescent markers. The new or improved techniques that have become available include immunocytochemistry using immunogold labeling techniques or fluorescent probes, cryopreservation and cryosectioning, in situ hybridization, fluorescent reporters for subcellular localization, micro-analytical methods for elemental distribution, confocal laser scanning microscopy, scanning tunneling microscopy and live-imaging. Taken together, these tools are providing both researchers and students with a novel and multidimensional view of the intricate biological processes during parasite development in the host.

Electron energy-loss spectroscopy as a tool for elemental analysis in biological speciments.

A transmission electron microscope (TEM) accessory, the energy filter, enables the establishment of a method for elemental microanalysis, the electron energy-loss spectroscopy (EELS). In conventional TEM, unscattered, elastic, and inelastic scattered electrons contribute to image information. Energy-filtering TEM (EFTEM) allows elemental analysis at the ultrastructural level by using selected inelastic scattered electrons. EELS is an excellent method for elemental microanalysis and nanoanalysis with good sensitivity and accuracy. However, it is a complex method whose potential is seldom completely exploited, especially for biological specimens. In addition to spectral analysis, parallel-EELS, we present two different imaging techniques in this chapter, namely electron spectroscopic imaging (ESI) and image-EELS. We aim to introduce these techniques in this chapter with the elemental microanalysis of titanium. Ultrafine, 22-nm titanium dioxide particles are used in an inhalation study in rats to investigate the distribution of nanoparticles in lung tissue.

REMOVING TECHNICAL VARIABILITY IN RNA-SEQ DATA USING CONDITIONAL QUANTILE NORMALIZATION

The ability to measure gene expression on a genome-wide scale is one of the most promising accomplishments in molecular biology. Microarrays, the technology that first permitted this, were riddled with problems due to unwanted sources of variability. Many of these problems are now mitigated, after a decade’s worth of statistical methodology development. The recently developed RNA sequencing (RNA-seq) technology has generated much excitement in part due to claims of reduced variability in comparison to microarrays. However, we show RNA-seq data demonstrates unwanted and obscuring variability similar to what was first observed in microarrays. In particular, we find GC-content has a strong sample specific effect on gene expression measurements that, if left uncorrected, leads to false positives in downstream results. We also report on commonly observed data distortions that demonstrate the need for data normalization. Here we describe statistical methodology that improves precision by 42% without loss of accuracy. Our resulting conditional quantile normalization (CQN) algorithm combines robust generalized regression to remove systematic bias introduced by deterministic features such as GC-content, and quantile normalization to correct for global distortions.