Analgesic Effects of Sweet-Tasting Solutions for Infants: Current State of Equipoise

OBJECTIVE: The goal was to review published studies of analgesic effects of sweet solutions, to ascertain areas with sufficient evidence of effectiveness and areas of uncertainty. METHODS: Databases searched included Medline, Embase, the Cumulative Index to Nursing and Allied Health Literature database, and PsycINFO, using the terms pain*, infant*, neonat*, newborn*, sucrose, glucose, and alternative sugars. Publications were sorted according to type, year, painful procedure studied, placebo/no-treatment groups, population studied, and country of publication. RESULTS: A total of 298 relevant unique publications involving human infants were identified; 125 (42%) were primary research studies, of which 116 (93%) were randomized controlled trials. Healthy preterm or term newborns were included in 82 studies (65%), and sick or very low birth weight infants were included in 22 (18%). Most studies included single episodes of painful procedures, with only 3 (2%) conducted over long periods. Procedures investigated most frequently were heel lance (49%), venipuncture (14%), and intramuscular injection (14%). Placebo or no-treatment groups were included in 111 studies (89%); in 103 (93%) of those studies, sweet solutions reduced behavioral responses, compared with placebo/no treatment. CONCLUSION: Clinical equipoise relating to analgesic effects of sweet solutions no longer exists for single episodes of procedures for healthy preterm and term newborn infants. Uncertainties include outcomes after prolonged use of sweet solutions, concomitant use of other analgesics, and effectiveness beyond the newborn period. Future research should focus on addressing these knowledge and research gaps. Pediatrics 2010;126:894-902

Online Mammographic Images Database for Development and Comparison of CAD Schemes

Considering the difficulties in finding good-quality images for the development and test of computer-aided diagnosis (CAD), this paper presents a public online mammographic images database free for all interested viewers and aimed to help develop and evaluate CAD schemes. The digitalization of the mammographic images is made with suitable contrast and spatial resolution for processing purposes. The broad recuperation system allows the user to search for different images, exams, or patient characteristics. Comparison with other databases currently available has shown that the presented database has a sufficient number of images, is of high quality, and is the only one to include a functional search system.

In silico analysis of candidate genes involved in light sensing and signal transduction pathways in soybean

Several aspects of photoperception and light signal transduction have been elucidated by studies with model plants. However, the information available for economically important crops, such as Fabaceae species, is scarce. In order to incorporate the existing genomic tools into a strategy to advance soybean research, we have investigated publicly available expressed sequence tag ( EST) sequence databases in order to identify Glycine max sequences related to genes involved in light-regulated developmental control in model plants. Approximately 38,000 sequences from open-access databases were investigated, and all bona fide and putative photoreceptor gene families were found in soybean sequence databases. We have identified G. max orthologs for several families of transcriptional regulators and cytoplasmic proteins mediating photoreceptor-induced responses, although some important Arabidopsis phytochrome-signaling components are absent. Moreover, soybean and Arabidopsis gene-family homologs appear to have undergone a distinct expansion process in some cases. We propose a working model of light perception, signal transduction and response-eliciting in G. max, based on the identified key components from Arabidopsis. These results demonstrate the power of comparative genomics between model systems and crop species to elucidate several aspects of plant physiology and metabolism.

Taenia crassiceps cysticerci: Characterization of the 14-kDa glycoprotein with homologies to antigens from Taenia solium cysticerci

Glycoproteins from the total vesicular fluid of Taenia crassiceps (VF-Tc) were prepared using three different purification methods, consisting of ConA-lectin affinity chromatography (ConA-Tc), preparative electrophoresis (SDS-PAGE) (14gp-Tc), and monoclonal antibody immunoaffinity chromatography (18/14-Tc). The complex composition represented by the VF-Tc and ConA-Tc antigens revealed peptides ranging from 101 - to 14-kDa and from 92- to 12-kDa, respectively. Immunoblotting using lectins confirmed glucose/mannose (glc/man) residues in the 18- and 14-kDa peptides, which are considered specific and immunodominant for the diagnosis of cysticercosis, and indicated that these fractions are glycoproteins. Serum antibodies from a patient with neurocysticercosis that reacted to the 14gp band from T. crassiceps (Tc) were eluted from immunoblotting membranes and showed reactivity to 14gp from Taenia solium. In order to determine the similar peptide sequence, the N-terminal amino acid was determined and analyzed with sequences available in public databases. This sequence revealed partial homology between T. crassiceps and T solium peptides. In addition, mass spectrometry along with theoretical M(r) and pI of the 14gp-Tc point suggested a close relationship to some peptides of a 150-kDa protein complex of the T solium previously described. The identification of these common immunogenic sites will contribute to future efforts to develop recombinant antigens and synthetic peptides for immunological assays. (C) 2009 Elsevier Inc. All rights reserved.

New information on carbohydrates in the Brazilian Food Composition Database

Foods that contain unavailable carbohydrates may lower the risks for some non-transmissible chronic diseases because of the potential benefits provided by the products of colonic fermentation. On the other hand, foods that are sources of available carbohydrates may have higher energy value and increase the post-prandial glycemic response. The biomarker glycemic index and the resulting glycemic load may be used to classify foods according to their potential to increase blood glucose. Information about glycemic index and glycemic load may be useful in diet therapy. Currently, food composition tables in Brazil do not provide data for individually analyzed carbohydrates even though some quality data are available in scientific publications. The objectives of this work were to produce and compile information about the concentration of individual carbohydrates in foods and their glycemic responses and to disseminate this information through the Brazilian Food Composition Database (TBCA-USP). The glycemic index and glycemic load of foods were evaluated in healthy individuals. Concentrations of available carbohydrates (soluble sugars and available starch) and unavailable carbohydrates (dietary fiber, resistant starch, beta-glucans, fructans) were quantified by official methods, and other national data were compiled. TBCA-USP (http://www.fcf.usp.br/tabela), which is used by professionals and the population in general, now offers both chemical and biological information for carbohydrates. (C) 2009 Elsevier Inc. All rights reserved.

The 2008 update of the Aspergillus nidulans genome annotation: A community effort

The identification and annotation of protein-coding genes is one of the primary goals of whole-genome sequencing projects, and the accuracy of predicting the primary protein products of gene expression is vital to the interpretation of the available data and the design of downstream functional applications. Nevertheless, the comprehensive annotation of eukaryotic genomes remains a considerable challenge. Many genomes submitted to public databases, including those of major model organisms, contain significant numbers of wrong and incomplete gene predictions. We present a community-based reannotation of the Aspergillus nidulans genome with the primary goal of increasing the number and quality of protein functional assignments through the careful review of experts in the field of fungal biology. (C) 2009 Elsevier Inc. All rights reserved.

Trypanocidal, leislimanicidal and antifungal potential from marine red alga Bostrychia tenella J. Agardli (Rhodomelaceae, Ceraniiales)

Specimens of the red alga Bostrychia tenella J Agardh (Rhodomelaceae, Ceramiales) were collected from the Sao Paulo coast and submitted to loom temperature solvent extraction The resulting extract was fractionated by partitioning with organic solvent The n-hexane (BT-H) and dichloromethane (BT-D) fractions showed antiprotozoal potential in biological tests with Trypanosoma cruzi and Leishmania amazonensis and presented high activity in an antifungal assay with the phytopathogenic fungi Cladosporium cladosporioides and Cladosporium sphaerospermum Chromatography methods were used to generate subfractions from BT-H (H01 to H11) and from BT-D (D01 to 019) The subtractions were analyzed by gas chromatography-mass spectrometry (GC/MS). and the substances were identified by retention index (Kovats) and by comparison to databases of commercial mass spectra The volatile compounds found in marine algae were identified as fatty acids, low molecular mass hydrocarbons, esters and steroids, some of these have been previously described in the literature based on other biological activities Moreover, uncommon substances. such as neophytadiene were also identified In a trypanocidal assay, fractions BT-H and BT-D showed IC(50) values of 168 and 19 1 mu g/mL. respectively, and were mote active than the gentian violet standard (31 mu g/ml.); subfractions H02. H03, D01 and D02 were active against L amasonensis, exhibiting IC(50) values of 1 S. 2 7, 4 4. and 4 3 mu g/mL., respectively (standard amphotericin B IC(50) = 13 mu g/mL.) All fractions showed antifungal potential this work reports the biological activity and identification of compounds by GC/MS for the marine red alga B tenella for the first time (C) 2010 Elsevier B V All lights reserved

Crotalus durissus collilineatus venom gland transcriptome: Analysis of gene expression profile

Crotalus durissus rattlesnakes are responsible for the most lethal cases of snakebites in Brazil. Crotalus durissus collilineatus subspecies is related to a great number of accidents in Southeast and Central West regions, but few studies on its venom composition have been carried out to date. In an attempt to describe the transcriptional profile of the C. durissus collilineatus venom gland, we generated a cDNA library and the sequences obtained could be identified by similarity searches on existing databases. Out of 673 expressed sequence tags (ESTs) 489 produced readable sequences comprising 201 singletons and 47 clusters of two or more ESTs. One hundred and fifty reads (60.5%) produced significant hits to known sequences. The results showed a predominance of toxin-coding ESTs instead of transcripts coding for proteins involved in all cellular functions. The most frequent toxin was crotoxin, comprising 88% of toxin-coding sequences. Crotoxin B, a basic phospholipase A(2) (PLA(2)) subunit of crotoxin, was represented in more variable forms comparing to the non-enzymatic subunit (crotoxin A), and most sequences coding this molecule were identified as CB1 isoform from Crotalus durissus terrificus venom. Four percent of toxin-related sequences in this study were identified as growth factors, comprising five sequences for vascular endothelial growth factor (VEGF) and one for nerve growth factor (NGF) that showed 100% of identity with C. durissus terrificus NGF. We also identified two clusters for metalloprotease from PII class comprising 3% of the toxins, and two for serine proteases, including gyroxin (2.5%). The remaining 2.5% of toxin-coding ESTs represent singletons identified as homologue sequences to cardiotoxin, convulxin, angiotensin-converting enzyme inhibitor and C-type natriuretic peptide, Ohanin, crotamin and PLA(2) inhibitor. These results allowed the identification of the most common classes of toxins in C. durissus collilineatus snake venom, also showing some unknown classes for this subspecies and even for C. durissus species, such as cardiotoxins and VEGF. (C) 2009 Published by Elsevier Masson SAS.

The prediction of disease risk in genomic medicine

In recent years, the phrase 'genomic medicine' has increasingly been used to describe a new development in medicine that holds great promise for human health. This new approach to health care uses the knowledge of an individual's genetic make-up to identify those that are at a higher risk of developing certain diseases and to intervene at an earlier stage to prevent these diseases. Identifying genes that are involved in disease aetiology will provide researchers with tools to develop better treatments and cures. A major role within this field is attributed to 'predictive genomic medicine', which proposes screening healthy individuals to identify those who carry alleles that increase their susceptibility to common diseases, such as cancers and heart disease. Physicians could then intervene even before the disease manifests and advise individuals with a higher genetic risk to change their behaviour - for instance, to exercise or to eat a healthier diet - or offer drugs or other medical treatment to reduce their chances of developing these diseases. These promises have fallen on fertile ground among politicians, health-care providers and the general public, particularly in light of the increasing costs of health care in developed societies. Various countries have established databases on the DNA and health information of whole populations as a first step towards genomic medicine. Biomedical research has also identified a large number of genes that could be used to predict someone's risk of developing a certain disorder. But it would be premature to assume that genomic medicine will soon become reality, as many problems remain to be solved. Our knowledge about most disease genes and their roles is far from sufficient to make reliable predictions about a patient’s risk of actually developing a disease. In addition, genomic medicine will create new political, social, ethical and economic challenges that will have to be addressed in the near future.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Development of a dietary supplement database

Data describing the composition of dietary supplements are not readily available to the public health community. As a result, intake from dietary supplements is generally not considered in most dietary surveys and, hence, little is known about the significance of supplement intake in relation to total diet or disease risk. To enable a more comprehensive analysis of dietary data, a database of the composition of various dietary supplements has been compiled. Active ingredients of all dietary supplements sold in Australia are included in the Australian Register of Therapeutic Goods (ARTG), maintained by the Therapeutic Goods Administration. Products included in the database were restricted to those vitamin, mineral and other supplements identified in dietary data collected from studies conducted in southeast Queensland and New South Wales (850 supplements). Conversion factors from ingredients compounds to active elements were compiled from standard sources. No account has been made for bioavailability, consistent with current practice for food composition databases. The database can be queried by ARTG identification number, brand, product title, or a variety of other fields. Expected future developments include development of standard formulations for use when supplements are incompletely specified, and expansion of products included for more widespread use.

Expressed sequenced tags and new genes from the cattle tick, Boophilus microplus

We used the expressed sequenced tags (ESTs) approach to study the genome of the cattle tick Boophilus microplus. One hundred and forty-two of our 234 unique ESTs were from genes not previously identified from ticks, mites or any other arachnids. The largest class of identified ESTs (29%) was from genes involved in transcription and translation. Ninety-one ESTs (39% of all ESTs) did not match any sequences in international databases; some of these may be specific to ticks. Thirteen percent of our ESTs were from ribosomal proteins and two ESTs were for genes implicated in resistance to pesticides. (C) 1998 Chapman & Hall Ltd.

Data partitioning for parallel spatial join processing

The cost of spatial join processing can be very high because of the large sizes of spatial objects and the computation-intensive spatial operations. While parallel processing seems a natural solution to this problem, it is not clear how spatial data can be partitioned for this purpose. Various spatial data partitioning methods are examined in this paper. A framework combining the data-partitioning techniques used by most parallel join algorithms in relational databases and the filter-and-refine strategy for spatial operation processing is proposed for parallel spatial join processing. Object duplication caused by multi-assignment in spatial data partitioning can result in extra CPU cost as well as extra communication cost. We find that the key to overcome this problem is to preserve spatial locality in task decomposition. We show in this paper that a near-optimal speedup can be achieved for parallel spatial join processing using our new algorithms.

Interval breast cancers in an Australian mammographic screening program

Objective: To determine the incidence of interval cancers which occurred in the first 12 months after mammographic screening at a mammographic screening service. Design: Retrospective analysis of data obtained by crossmatching the screening Service and the New South Wales Central Cancer Registry databases. Setting: The Central & Eastern Sydney Service of BreastScreen NSW. Participants: Women aged 40-69 years at first screen, who attended for their first or second screen between 1 March 1988 and 31 December 1992. Main outcome measures: Interval-cancer rates per 10 000 screens and as a proportion of the underlying incidence of breast cancer (as estimated by the underlying rate in the total NSW population). Results: The 12-month interval-cancer incidence per 10 000 screens was 4.17 for the 40-49 years age group (95% confidence interval [CI], 1.35-9.73) and 4.64 for the 50-69 years age group (95% CI, 2.47-7.94). Proportional incidence rates were 30.1% for the 40-49 years age group (95% CI, 9.8-70.3) and 22% for the 50-69 years age group (95% CI, 11.7-37.7). There was no significant difference between the proportional incidence rate for the 50-69 years age group for the Central & Eastern Sydney Service and those of major successful overseas screening trials. Conclusion: Screening quality was acceptable and should result in a significant mortality reduction in the screened population. Given the small number of cancers involved, comparison of interval-cancer statistics of mammographic screening programs with trials requires age-specific or age-adjusted data, and consideration of confidence intervals of both program and trial data.

Unsupervised cell nucleus segmentation with active contours

The task of segmenting cell nuclei from cytoplasm in conventional Papanicolaou (Pap) stained cervical cell images is a classical image analysis problem which may prove to be crucial to the development of successful systems which automate the analysis of Pap smears for detection of cancer of the cervix. Although simple thresholding techniques will extract the nucleus in some cases, accurate unsupervised segmentation of very large image databases is elusive. Conventional active contour models as introduced by Kass, Witkin and Terzopoulos (1988) offer a number of advantages in this application, but suffer from the well-known drawbacks of initialisation and minimisation. Here we show that a Viterbi search-based dual active contour algorithm is able to overcome many of these problems and achieve over 99% accurate segmentation on a database of 20 130 Pap stained cell images. (C) 1998 Elsevier Science B.V. All rights reserved.