Revisiting a medical case of "stinging" in the human oral cavity caused by ingestion of raw squid (Cephalopoda: Teuthida): new data on the functioning of squid's spermatophores

Male squid produce intricate spermatophores that, when transferred to the female, undergo the spermatophoric reaction, a complex process of evagination that leads to the attachment of the spermatangium, that is, the everted spermatophore containing the sperm mass. While this process is still not completely understood, the medical literature includes several reports of "oral stinging" (i.e., punctured wounds in the human oral cavity) following consumption of raw male squid, which contains undischarged spermatophores able to inflict such wounds. Here, we revisit a recent medical report of oral stinging by Shiraki et al. (Pathol Int 61:749-751, 2011), providing an in-depth reanalysis of their histological biopsies and revealing vital information on the functioning of squid spermatophores. The morphology of the spermatangia attached within the oral cavity is similar to the condition found in spermatangia naturally attached to female squids. The spermatangia were able to superficially puncture the superficial layers of the oral stratified squamous epithelium, and numerous, minute stellate particles from the squid spermatophore were found adhered to the oral epithelium. These findings corroborate previous hypotheses on the functioning of squid spermatophores, namely that spermatophore attachment generally involves tissue scarification, and that stellate particles play a vital role in the attachment process. Moreover, spermatophore attachment is confirmed to be autonomous (i.e., performed by the spermatophore itself) in another squid species (possibly a loliginid), and the results strongly indicate that the attachment mechanism is not dependent upon a specialized epithelium, nor a mate's specific chemical stimulus. From the pathological point of view, the best prophylactic measure at present is the removal of the internal organs of the raw squid prior to its consumption.

The SB-index and the HSB-index: efficient indices for spatial data warehouses

Spatial data warehouses (SDWs) allow for spatial analysis together with analytical multidimensional queries over huge volumes of data. The challenge is to retrieve data related to ad hoc spatial query windows according to spatial predicates, avoiding the high cost of joining large tables. Therefore, mechanisms to provide efficient query processing over SDWs are essential. In this paper, we propose two efficient indices for SDW: the SB-index and the HSB-index. The proposed indices share the following characteristics. They enable multidimensional queries with spatial predicate for SDW and also support predefined spatial hierarchies. Furthermore, they compute the spatial predicate and transform it into a conventional one, which can be evaluated together with other conventional predicates by accessing a star-join Bitmap index. While the SB-index has a sequential data structure, the HSB-index uses a hierarchical data structure to enable spatial objects clustering and a specialized buffer-pool to decrease the number of disk accesses. The advantages of the SB-index and the HSB-index over the DBMS resources for SDW indexing (i.e. star-join computation and materialized views) were investigated through performance tests, which issued roll-up operations extended with containment and intersection range queries. The performance results showed that improvements ranged from 68% up to 99% over both the star-join computation and the materialized view. Furthermore, the proposed indices proved to be very compact, adding only less than 1% to the storage requirements. Therefore, both the SB-index and the HSB-index are excellent choices for SDW indexing. Choosing between the SB-index and the HSB-index mainly depends on the query selectivity of spatial predicates. While low query selectivity benefits the HSB-index, the SB-index provides better performance for higher query selectivity.

Biventricular structural and functional responses to aortic constriction in a rabbit model of chronic right ventricular pressure overload

Objectives: Chronic right ventricular (RV) pressure overload results in pathologic RV hypertrophy and diminished RV function. Although aortic constriction has been shown to improve systolic function in acute RV failure, its effect on RV responses to chronic pressure overload is unknown. Methods: Adjustable vascular banding devices were placed on the main pulmonary artery and descending aorta. In 5 animals (sham group), neither band was inflated. In 9 animals (PAB group), only the pulmonary arterial band was inflated, with adjustments on a weekly basis to generate systemic or suprasystemic RV pressure at 28 days. In 9 animals, both pulmonary arterial and aortic devices were inflated (PAB+AO group), the pulmonary arterial band as for the PAB group and the aortic band adjusted to increase proximal systolic blood pressure by approximately 20 mm Hg. Effects on the functional performance were assessed 5 weeks after surgery by conductance catheters, followed by histologic and molecular assessment. Results: Contractile performance was significantly improved in the PAB+AO group versus the PAB group for both ventricles. Relative to sham-operated animals, both banding groups showed significant differences in myocardial histologic and molecular responses. Relative to the PAB group, the PAB+AO group showed significantly decreased RV cardiomyocyte diameter, decreased RV collagen content, and reduced RV expression of endothelin receptor type B, matrix metalloproteinase 9, and transforming growth factor beta genes. Conclusions: Aortic constriction in an experimental model of chronic RV pressure overload not only resulted in improved biventricular systolic function but also improved myocardial remodeling. These data suggest that chronically increased left ventricular afterload leads to a more physiologically hypertrophic response in the pressure-overloaded RV. (J Thorac Cardiovasc Surg 2012;144:1494-501)

Spatial-temporal variations in phytoplankton size and colored detrital matter absorption at global and regional scales, as derived from twelve years of SeaWiFS data (1998-2009)

A procedure has been proposed by Ciotti and Bricaud (2006) to retrieve spectral absorption coefficients of phytoplankton and colored detrital matter (CDM) from satellite radiance measurements. This was also the first procedure to estimate a size factor for phytoplankton, based on the shape of the retrieved algal absorption spectrum, and the spectral slope of CDM absorption. Applying this method to the global ocean color data set acquired by SeaWiFS over twelve years (1998-2009), allowed for a comparison of the spatial variations of chlorophyll concentration ([Chl]), algal size factor (S-f), CDM absorption coefficient (a(cdm)) at 443 nm, and spectral slope of CDM absorption (S-cdm). As expected, correlations between the derived parameters were characterized by a large scatter at the global scale. We compared temporal variability of the spatially averaged parameters over the twelve-year period for three oceanic areas of biogeochemical importance: the Eastern Equatorial Pacific, the North Atlantic and the Mediterranean Sea. In all areas, both S-f and a(cdm)(443) showed large seasonal and interannual variations, generally correlated to those of algal biomass. The CDM maxima appeared in some occasions to last longer than those of [Chl]. The spectral slope of CDM absorption showed very large seasonal cycles consistent with photobleaching, challenging the assumption of a constant slope commonly used in bio-optical models. In the Equatorial Pacific, the seasonal cycles of [Chl], S-f, a(cdm)(443) and S-cdm, as well as the relationships between these parameters, were strongly affected by the 1997-98 El Ni o/La Ni a event.

Ethnic Influence in Clinical and Functional Measures of Brazilian Patients with Spondyloarthritis

Objective. Spondyloarthritides (SpA) can present different disease spectra according to ethnic background. The Brazilian Registry of Spondyloarthritis (RBE) is a nationwide registry that comprises a large databank on clinical, functional, and treatment data on Brazilian patients with SpA. The aim of our study was to analyze the influence of ethnic background in SpA disease patterns in a large series of Brazilian patients. Methods. A common protocol of investigation was prospectively applied to 1318 SpA patients in 29 centers distributed through the main geographical regions in Brazil. The group comprised whites (65%), African Brazilians (31.3%), and people of mixed origins (3.7%). Clinical and demographic variables and various disease index scores were compiled. Ankylosing spondylitis (AS) was the most frequent disease in the group (65.1%); others were psoriatic arthritis (18.3%), undifferentiated SpA (6.8%), enteropathic arthritis (3.7%), and reactive arthritis (3.4%). Results. White patients were significantly associated with psoriasis (p = 0.002), positive HLA-B27 (p = 0.014), and use of corticosteroids (p < 0.0001). Hip involvement (p = 0.02), axial inflammatory pain (p = 0.04), and radiographic sacroiliitis (p = 0.025) were associated with African Brazilian descent. Sex distribution, family history, and presence of peripheral arthritis, uveitis, dactylitis, urethritis, and inflammatory bowel disease were similar in the 3 groups, as well as age at disease onset, time from first symptom until diagnosis, and use of anti-tumor necrosis factor-a agents (p > 0.05). Schober test and thoracic expansion were similar in the 3 groups, whereas African Brazilians had higher Maastricht Ankylasing Spondylitis Enthesitis Scores (p = 0.005) and decreased lateral lumbar flexion (p = 0.003), while whites had a higher occiput-to-wall distance (p = 0.02). African Brazilians reported a worse patient global assessment of disease (p = 0.011). Other index scores and prevalence of work incapacity were similar in the 3 groups, although African Brazilians had worse performance in the Ankylosing Spondylitis Quality of Life questionnaire (p < 0.001). Conclusion. Ethnic background is associated with distinct clinical aspects of SpA in Brazilian patients. African Brazilian patients with SpA have a poorer quality of life and report worse disease compared to whites, (First Release Nov 1 2011; J Rheumatol 2012;39:141-7; doi:10.3899/jrheum.110372)

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Computational framework to support integration of biomolecular and clinical data within a translational approach

Background The use of the knowledge produced by sciences to promote human health is the main goal of translational medicine. To make it feasible we need computational methods to handle the large amount of information that arises from bench to bedside and to deal with its heterogeneity. A computational challenge that must be faced is to promote the integration of clinical, socio-demographic and biological data. In this effort, ontologies play an essential role as a powerful artifact for knowledge representation. Chado is a modular ontology-oriented database model that gained popularity due to its robustness and flexibility as a generic platform to store biological data; however it lacks supporting representation of clinical and socio-demographic information. Results We have implemented an extension of Chado – the Clinical Module - to allow the representation of this kind of information. Our approach consists of a framework for data integration through the use of a common reference ontology. The design of this framework has four levels: data level, to store the data; semantic level, to integrate and standardize the data by the use of ontologies; application level, to manage clinical databases, ontologies and data integration process; and web interface level, to allow interaction between the user and the system. The clinical module was built based on the Entity-Attribute-Value (EAV) model. We also proposed a methodology to migrate data from legacy clinical databases to the integrative framework. A Chado instance was initialized using a relational database management system. The Clinical Module was implemented and the framework was loaded using data from a factual clinical research database. Clinical and demographic data as well as biomaterial data were obtained from patients with tumors of head and neck. We implemented the IPTrans tool that is a complete environment for data migration, which comprises: the construction of a model to describe the legacy clinical data, based on an ontology; the Extraction, Transformation and Load (ETL) process to extract the data from the source clinical database and load it in the Clinical Module of Chado; the development of a web tool and a Bridge Layer to adapt the web tool to Chado, as well as other applications. Conclusions Open-source computational solutions currently available for translational science does not have a model to represent biomolecular information and also are not integrated with the existing bioinformatics tools. On the other hand, existing genomic data models do not represent clinical patient data. A framework was developed to support translational research by integrating biomolecular information coming from different “omics” technologies with patient’s clinical and socio-demographic data. This framework should present some features: flexibility, compression and robustness. The experiments accomplished from a use case demonstrated that the proposed system meets requirements of flexibility and robustness, leading to the desired integration. The Clinical Module can be accessed in http://dcm.ffclrp.usp.br/caib/pg=iptrans webcite.

Seeking tools for image fusion between computed tomography, structural and functional magnetic resonance methods for applications in neurosurgery

OBJECTIVE: To evaluate tools for the fusion of images generated by tomography and structural and functional magnetic resonance imaging. METHODS: Magnetic resonance and functional magnetic resonance imaging were performed while a volunteer who had previously undergone cranial tomography performed motor and somatosensory tasks in a 3-Tesla scanner. Image data were analyzed with different programs, and the results were compared. RESULTS: We constructed a flow chart of computational processes that allowed measurement of the spatial congruence between the methods. There was no single computational tool that contained the entire set of functions necessary to achieve the goal. CONCLUSION: The fusion of the images from the three methods proved to be feasible with the use of four free-access software programs (OsiriX, Register, MRIcro and FSL). Our results may serve as a basis for building software that will be useful as a virtual tool prior to neurosurgery.

Expression analysis and in silico characterization of intronic long noncoding RNAs in renal cell carcinoma: emerging functional associations

Abstract Background Intronic and intergenic long noncoding RNAs (lncRNAs) are emerging gene expression regulators. The molecular pathogenesis of renal cell carcinoma (RCC) is still poorly understood, and in particular, limited studies are available for intronic lncRNAs expressed in RCC Methods Microarray experiments were performed with custom-designed arrays enriched with probes for lncRNAs mapping to intronic genomic regions. Samples from 18 primary RCC tumors and 11 nontumor adjacent matched tissues were analyzed. Meta-analyses were performed with microarray expression data from three additional human tissues (normal liver, prostate tumor and kidney nontumor samples), and with large-scale public data for epigenetic regulatory marks and for evolutionarily conserved sequences. Results A signature of 29 intronic lncRNAs differentially expressed between RCC and nontumor samples was obtained (false discovery rate (FDR) <5%). A signature of 26 intronic lncRNAs significantly correlated with the RCC five-year patient survival outcome was identified (FDR <5%, p-value ≤0.01). We identified 4303 intronic antisense lncRNAs expressed in RCC, of which 22% were significantly (p <0.05) cis correlated with the expression of the mRNA in the same locus across RCC and three other human tissues. Gene Ontology (GO) analysis of those loci pointed to 'regulation of biological processes’ as the main enriched category. A module map analysis of the protein-coding genes significantly (p <0.05) trans correlated with the 20% most abundant lncRNAs, identified 51 enriched GO terms (p <0.05). We determined that 60% of the expressed lncRNAs are evolutionarily conserved. At the genomic loci containing the intronic RCC-expressed lncRNAs, a strong association (p <0.001) was found between their transcription start sites and genomic marks such as CpG islands, RNA Pol II binding and histones methylation and acetylation. Conclusion Intronic antisense lncRNAs are widely expressed in RCC tumors. Some of them are significantly altered in RCC in comparison with nontumor samples. The majority of these lncRNAs is evolutionarily conserved and possibly modulated by epigenetic modifications. Our data suggest that these RCC lncRNAs may contribute to the complex network of regulatory RNAs playing a role in renal cell malignant transformation.

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

With the increasing production of information from e-government initiatives, there is also the need to transform a large volume of unstructured data into useful information for society. All this information should be easily accessible and made available in a meaningful and effective way in order to achieve semantic interoperability in electronic government services, which is a challenge to be pursued by governments round the world. Our aim is to discuss the context of e-Government Big Data and to present a framework to promote semantic interoperability through automatic generation of ontologies from unstructured information found in the Internet. We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area. The results achieved in this study are based on the architectural definition and major components and requirements in order to compose the proposed framework. With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society.