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Recovery of image blocks using the method of alternating projections.

A technique for block-loss restoration in block-based image and video coding, dubbed recovery of image blocks using the method of alternating projections (RIBMAP), is developed. The algorithm is based on orthogonal projections onto constraint sets in a Hilbert space. For the recovery of a linear dimension N size block, a total of 8N vectors are extracted from the surrounding area of an N x N missing block. These vectors form a library from which the best matching spatial information for the missing block is extracted. Recovery vectors, including both undamaged and restored damaged pixels, are introduced. The vectors are used to find highly correlated information relating to the lost pixels. To assure continuity with the surrounding undamaged area, three additional convex constraints are formulated. Adherance to these sets is imposed using alternating projections. Simulation results using orthogonal projections demonstrate that RIBMAP recovers spatial structure faithfully. Simulation comparisons with other procedures are presented: Ancis and Giusto's hybrid edge-based average-median interpolation technique, Sun and Kwok's projections onto convex sets-based method, Hemami and Meng's interblock correlation interpolation approach, Shirani et al.'s modified interblock correlation interpolation scheme, and Alkachouh and Bellanger's fast discrete cosine transformation-based spatial domain interpolation algorithm. Characteristic of the results are those of the "Lena" JPEG image when one fourth of periodically spaced blocks in the image have errors. The peak signal-to-noise ratio of the restored image is 28.68, 29.99, 31.86, 31.69, 31.57, and 34.65 dB using that of Ancis and Giusto, Sun and Kwok, Hemami and Meng, Shirani et al., Alkachouh and Bellanger, and RIPMAP, respectively.

Algorithms↗

Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data.

BACKGROUND: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfunction of the rod and cone photoreceptor cells. Development and maintenance of photoreceptors requires appropriate regulation of the many genes specifically or highly expressed in these cells. Over the last decades, different experimental approaches have been developed to identify photoreceptor enriched genes. Recent progress in RNA analysis technology has generated large amounts of gene expression data relevant to retinal development. This paper assesses a machine learning methodology for supporting the identification of photoreceptor enriched genes based on expression data. RESULTS: Based on the analysis of publicly-available gene expression data from the developing mouse retina generated by serial analysis of gene expression (SAGE), this paper presents a predictive methodology comprising several in silico models for detecting key complex features and relationships encoded in the data, which may be useful to distinguish genes in terms of their functional roles. In order to understand temporal patterns of photoreceptor gene expression during retinal development, a two-way cluster analysis was firstly performed. By clustering SAGE libraries, a hierarchical tree reflecting relationships between developmental stages was obtained. By clustering SAGE tags, a more comprehensive expression profile for photoreceptor cells was revealed. To demonstrate the usefulness of machine learning-based models in predicting functional associations from the SAGE data, three supervised classification models were compared. The results indicated that a relatively simple instance-based model (KStar model) performed significantly better than relatively more complex algorithms, e.g. neural networks. To deal with the problem of functional class imbalance occurring in the dataset, two data re-sampling techniques were studied. A random over-sampling method supported the implementation of the most powerful prediction models. The KStar model was also able to achieve higher predictive sensitivities and specificities using random over-sampling techniques. CONCLUSION: The approaches assessed in this paper represent an efficient and relatively inexpensive in silico methodology for supporting large-scale analysis of photoreceptor gene expression by SAGE. They may be applied as complementary methodologies to support functional predictions before implementing more comprehensive, experimental prediction and validation methods. They may also be combined with other large-scale, data-driven methods to facilitate the inference of transcriptional regulatory networks in the developing retina. Furthermore, the methodology assessed may be applied to other data domains.

Animals↗

A continuous high-resolution physical map spanning 17 megabases of the q12, q13.1, and q13.2 cytogenetic bands of human chromosome 19.

We report the construction of a high-resolution physical map of a 17-Mb region that encompasses the entire q12, q13.1, and q13.2 bands of human chromosome 19. The continuous map extends from a region approximately 400 kb centromeric of the D19S7 marker to the excision repair cross-complementing rodent repair deficiency complementation group 1 (ERCC1) locus. The ordered clone map has been obtained starting from a foundation of cosmid contigs assembled by automated fingerprinting and localized to the cytogenetic map by fluorescence in situ hybridization (FISH). Clonal continuity of the map has been achieved by binning and linking the premapped cosmid contigs by means of yeast artificial chromosomes (YACs). The map consists of a single contig composed of 169 YAC members (minimal spanning path of 18 YACs) linking 165 cosmid contigs. Eighty percent, or about 13.2 Mb of the entire region spanned by the map, has been resolved to the EcoRI restriction map level. Twenty-nine sequence-tagged sites associated with genetic markers or derived from FISH-mapped cosmids have been placed on the map. In addition to the ERCC1 gene area, the map includes the location of the creatine kinase muscle locus (CKM), imidazoledipetidase (PEPD), glucophosphate isomerase (GPI), myelin-associated glycoprotein (MAG), the apolipoprotein E and C (APOE and APOC) genes, and the ryanodine receptor (RYR1) gene. This type of map provides a source of continuously overlapping DNA segments at a level of resolution two orders of magnitude higher than that obtained using YACs alone. In addition, it provides ready-to-use reagents for detailed analyses at the gene level, FISH studies of chromosomal aberrations, and DNA sequencing.

Chromosome Mapping↗

NIH Consensus Statement on Management of Hepatitis C: 2002.

OBJECTIVE: To provide health care providers, patients, and the general public with a responsible assessment of currently available data regarding the management and treatment of hepatitis C. PARTICIPANTS: A non-Federal, nonadvocate, 12-member panel representing the fields of infectious diseases, gastroenterology, medical oncology, molecular genetics, geriatrics, internal medicine, and the public. In addition, experts in these same fields presented data to the panel and to a conference audience of approximately 300. EVIDENCE: Presentations by experts; a systematic review of the medical literature provided by the Agency for Healthcare Research and Quality; and an extensive bibliography of hepatitis C research papers, prepared by the National Library of Medicine. Scientific evidence was given precedence over clinical anecdotal experience. CONFERENCE PROCESS: Answering predefined questions, the panel drafted a statement based on the scientific evidence presented in open forum and the scientific literature. The draft statement was read in its entirety on the final day of the conference and circulated to the experts and the audience for comment. The panel then met in executive session to consider these comments and released a revised statement at the end of the conference. The statement was made available on the World Wide Web at http://consensus.nih.gov immediately after the conference. This statement is an independent report of the panel and is not a policy statement of the NIH or the Federal Government. CONCLUSIONS: The incidence of newly acquired hepatitis C infection has diminished in the United States. This decline is largely due to a decrease in cases among IDUs for reasons that are unclear and, to a lesser extent, to testing of blood donors for HCV. The virus is transmitted by blood and such transmission now occurs primarily through injection drug use, sex with an infected partner or multiple partners, and occupational exposure. The majority of infections become chronic, and therefore the prevalence of HCV infections is high, with about 3 million Americans now estimated to be chronically infected. HCV is a leading cause of cirrhosis, a common cause of HCC and the leading cause of liver transplantation in the United States. The disease spectrum associated with HCV infection varies greatly. Various studies have suggested that 3 to 20 percent of chronically infected patients will develop cirrhosis over a 20-year period, and these patients are at risk for HCC. Persons who are older at the time of infection, patients with continuous exposure to alcohol, and those co-infected with HIV or HBV demonstrate accelerated progression to more advanced liver disease. Conversely, individuals infected at a younger age have little or no disease progression over several decades. The diagnosis of chronic hepatitis C infection is often suggested by abnormalities in ALT levels and is established by EIA followed by confirmatory determination of HCV RNA. Several sensitive and specific assays are now partly automated for the purposes of detecting HCV RNA and quantifying the viral level. Although there is little correlation between viral level and disease manifestations, these assays have proven useful in identifying those patients who are more likely to benefit from treatment and, particularly, in demonstrating successful response to treatment as defined by an SVR. Liver biopsy is useful in defining baseline abnormalities of liver disease and in enabling patients and healthcare providers to reach a decision regarding antiviral therapy. Noninvasive tests do not currently provide the information that can be obtained through liver biopsy. Information on the genotype of the virus is important to guide treatment decisions. Genotype 1, most commonly found in the United States, is less amenable to treatment than genotypes 2 or 3. Therefore, clinical trials of antiviral therapies require genotyping information for appropriate stratification of subjects. Recent therapeutic trials in defined, selected populations have clearly shown that combinations of interferons and ribavirin are more effective than monotherapy. Moreover, trials using pegylated interferons have yielded improved SVR rates with similar toxicity profiles. However, results continue to show that the SVR rate is less common in patients with genotype 1 infections, higher HCV RNA levels, or more advanced stages of fibrosis. Genotype 1 infections require therapy for 48 weeks, whereas shorter treatment is feasible in genotype 2 and 3 infections. In genotype 1, the lack of an early virologic response (< 2 log decrease in HCV RNA) is associated with failure to achieve an SVR. The SVR is lower in patients with advanced liver disease than in patients without cirrhosis. Ongoing trials are exploring the usefulness of combination therapy in various populations. Preliminary experience in IDUs, individuals co-infected with HIV, children, and other special groups suggests similar responses are achievable in these populations. Patients with acute hepatitis C may be treated, but specific recommendations for antiviral treatment must await further evaluation of the rate of spontaneous clearance of the virus and determination of the optimal time to initiate treatment. Preventive measures beyond blood-banking practices include prompt identification of infected individuals, awareness of the potential for perinatal transmission, implementation of safe-injection practices, linkage of drug users to drug treatment programs, and implementation of community-based education and support programs to modify risk behavior. Some of these measures have been successfully implemented in the control of HIV infections, and it stands to reason that they would be valuable for reducing HCV transmission. Future advances in the diagnosis and management of hepatitis C require continued vigilance concerning the transmission of this infection, extending treatment to populations not previously evaluated in treatment trials, and the introduction of more effective therapies.

Acute Disease↗

Support vector machines for separation of mixed plant-pathogen EST collections based on codon usage.

MOTIVATION: Discovery of host and pathogen genes expressed at the plant-pathogen interface often requires the construction of mixed libraries that contain sequences from both genomes. Sequence identification requires high-throughput and reliable classification of genome origin. When using single-pass cDNA sequences difficulties arise from the short sequence length, the lack of sufficient taxonomically relevant sequence data in public databases and ambiguous sequence homology between plant and pathogen genes. RESULTS: A novel method is described, which is independent of the availability of homologous genes and relies on subtle differences in codon usage between plant and fungal genes. We used support vector machines (SVMs) to identify the probable origin of sequences. SVMs were compared to several other machine learning techniques and to a probabilistic algorithm (PF-IND) for expressed sequence tag (EST) classification also based on codon bias differences. Our software (Eclat) has achieved a classification accuracy of 93.1% on a test set of 3217 EST sequences from Hordeum vulgare and Blumeria graminis, which is a significant improvement compared to PF-IND (prediction accuracy of 81.2% on the same test set). EST sequences with at least 50 nt of coding sequence can be classified using Eclat with high confidence. Eclat allows training of classifiers for any host-pathogen combination for which there are sufficient classified training sequences. AVAILABILITY: Eclat is freely available on the Internet (http://mips.gsf.de/proj/est) or on request as a standalone version. CONTACT: friedel@informatik.uni-muenchen.de.

Algorithms↗

High throughput profile-profile based fold recognition for the entire human proteome.

BACKGROUND: In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power. In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. RESULTS: We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. CONCLUSION: This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.

Algorithms↗

Teaching pathology in the 21st century. An experimental automated curriculum delivery system for basic pathology.

In late 1984, the "General Professional Education of the Physician" (GPEP) report recommended, among other things, that medical curricula be revised to rely less on lectures and more on independent study and problem solving. We seem to have anticipated, in 1980, the findings of the GPEP panel by formulating and starting to test the hypothesis that certain "core" information in medical curricula can be as effectively delivered by technology-based self-study means as by lecture or formal laboratory. We began, at that time, to prepare a series of self-study materials using, at first, videotape and then computer-controlled optical videodiscs. The content area selected for study was basic microscopic pathology. The series was planned to cover the following areas of study: cellular alterations and adaptations, cell injury, acute inflammation, chronic inflammation and wound healing, cellular accumulations, circulatory disturbances, necrosis, and neoplasia. All are intended to provide learning experiences in basic pathology. The first two programs were released for testing in 1983 as a two-sided videodisc accompanied by computer-driven pretests, study modules, and posttests that used Apple computers and Pioneer (DiscoVision) videodisc players. An MS DOS (eg, IBM) version of the computer programs was released in 1984. The first two programs are now used in 57 US, Canadian, European, and Philippine health professions schools, and over 1300 student and faculty evaluations have been received. Student and faculty evaluations of these first two programs were very positive, and, as a result, the others are in production and will be completed in 1988. Only when a critical mass of curriculum is available can we really test our stated hypothesis. In the meantime, it is worthwhile to report the evaluation of the first two programs.

Audiovisual Aids↗

RENEX: an expert system for the interpretation of 99mTc-MAG3 scans to detect renal obstruction.

UNLABELLED: A renal expert system (RENEX) has been developed to assist physicians detect renal obstruction in patients undergoing pre- and postfurosemide 99mTc-mercaptoacetyltriglycine (99mTc-MAG3) scans. RENEX uses quantitative parameters extracted from the dynamic renal scan data and heuristic rules in the form of a knowledge base (KB) obtained from expert interpreters to conclude whether a kidney is obstructed. METHODS: Normal limits were established for 47 quantitative parameters extracted from the 99mTc-MAG3 scans of 100 potential renal donors. From these data the domain expert estimated 5 boundary conditions for each parameter: (i) definitely abnormal, (ii) probably abnormal, (iii) equivocal, (iv) probably normal, and (v) definitely normal. A sigmoid-type curve was then generated from these 5 boundary conditions, creating a parameter knowledge library used for converting the value of a prospective patient's individual quantitative parameters to a certainty factor (CF). Sixty heuristic rules were extracted from the domain expert to generate the KB for detecting obstruction. A forward-chaining inference engine was developed using the MYCIN combinatories (an approximation of Bayes theorem) to determine obstruction. A justification engine was implemented, which recorded the sequence of each rule that was fired and the current CF value of all input and output parameters at the time of instantiation to track and justify the logic of the conclusions. The entire system was fine tuned and tested using a pilot group of 32 patients (11 males, 21 females; mean age, 56.8 +/- 17.2 y; 63 kidneys) deemed by an expert panel to have 41 unobstructed kidneys, 13 obstructed kidneys,and 9 equivocal findings. RESULTS: RENEX agreed with the expert panel in 92% (12/13) of the obstructed kidneys, 93% (38/41) of the unobstructed kidneys, and 78% (7/9) of the kidneys interpreted as equivocal for obstructions. Processing time per patient was practically instantaneous using a 3.0-GHz personal computer programmed using interactive data language. CONCLUSION: We have developed a renal expert system for detecting renal obstruction using pre- and postfurosemide 99mTc-MAG3 renal scans, at a standardized expert level. These encouraging preliminary results warrant a prospective study in a large population of patients with and without renal obstruction to establish the diagnostic performance of this system.

Expert Systems↗

MIMOX: a web tool for phage display based epitope mapping.

BACKGROUND: Phage display is widely used in basic research such as the exploration of protein-protein interaction sites and networks, and applied research such as the development of new drugs, vaccines, and diagnostics. It has also become a promising method for epitope mapping. Research on new algorithms that assist and automate phage display based epitope mapping has attracted many groups. Most of the existing tools have not been implemented as an online service until now however, making it less convenient for the community to access, utilize, and evaluate them. RESULTS: We present MIMOX, a free web tool that helps to map the native epitope of an antibody based on one or more user supplied mimotopes and the antigen structure. MIMOX was coded in Perl using modules from the Bioperl project. It has two sections. In the first section, MIMOX provides a simple interface for ClustalW to align a set of mimotopes. It also provides a simple statistical method to derive the consensus sequence and embeds JalView as a Java applet to view and manage the alignment. In the second section, MIMOX can map a single mimotope or a consensus sequence of a set of mimotopes, on to the corresponding antigen structure and search for all of the clusters of residues that could represent the native epitope. NACCESS is used to evaluate the surface accessibility of the candidate clusters; and Jmol is embedded to view them interactively in their 3D context. Initial case studies show that MIMOX can reproduce mappings from existing tools such as FINDMAP and 3DEX, as well as providing novel, rational results. CONCLUSION: A web-based tool called MIMOX has been developed for phage display based epitope mapping. As a publicly available online service in this area, it is convenient for the community to access, utilize, and evaluate, complementing other existing programs. MIMOX is freely available at http://web.kuicr.kyoto-u.ac.jp/~hjian/mimox.

Bacteriophages↗

Clustering binary fingerprint vectors with missing values for DNA array data analysis.

Oligonucleotide fingerprinting is a powerful DNA array based method to characterize cDNA and ribosomal RNA gene (rDNA) libraries and has many applications including gene expression profiling and DNA clone classification. We are especially interested in the latter application. A key step in the method is the cluster analysis of fingerprint data obtained from DNA array hybridization experiments. Most of the existing approaches to clustering use (normalized) real intensity values and thus do not treat positive and negative hybridization signals equally (positive signals are much more emphasized). In this paper, we consider a discrete approach. Fingerprint data are first normalized and binarized using control DNA clones. Because there may exist unresolved (or missing) values in this binarization process, we formulate the clustering of (binary) oligonucleotide fingerprints as a combinatorial optimization problem that attempts to identify clusters and resolve the missing values in the fingerprints simultaneously. We study the computational complexity of this clustering problem and a natural parameterized version, and present an efficient greedy algorithm based on MINIMUM CLIQUE PARTITION on graphs. The algorithm takes advantage of some unique properties of the graphs considered here, which allow us to efficiently find the maximum cliques as well as some special maximal cliques. Our experimental results on simulated and real data demonstrate that the algorithm runs faster and performs better than some popular hierarchical and graph-based clustering methods. The results on real data from DNA clone classification also suggest that this discrete approach is more accurate than clustering methods based on real intensity values, in terms of separating clones that have different characteristics with respect to the given oligonucleotide probes.

Algorithms↗

Integrated and sequence-ordered BAC- and YAC-based physical maps for the rat genome.

As part of the effort to sequence the genome of Rattus norvegicus, we constructed a physical map comprised of fingerprinted bacterial artificial chromosome (BAC) clones from the CHORI-230 BAC library. These BAC clones provide approximately 13-fold redundant coverage of the genome and have been assembled into 376 fingerprint contigs. A yeast artificial chromosome (YAC) map was also constructed and aligned with the BAC map via fingerprinted BAC and P1 artificial chromosome clones (PACs) sharing interspersed repetitive sequence markers with the YAC-based physical map. We have annotated 95% of the fingerprint map clones in contigs with coordinates on the version 3.1 rat genome sequence assembly, using BAC-end sequences and in silico mapping methods. These coordinates have allowed anchoring 358 of the 376 fingerprint map contigs onto the sequence assembly. Of these, 324 contigs are anchored to rat genome sequences localized to chromosomes, and 34 contigs are anchored to unlocalized portions of the rat sequence assembly. The remaining 18 contigs, containing 54 clones, still require placement. The fingerprint map is a high-resolution integrative data resource that provides genome-ordered associations among BAC, YAC, and PAC clones and the assembled sequence of the rat genome.

Animals↗

Recognizing the fold of a protein structure.

This paper reports a graph-theoretic program, GRATH, that rapidly, and accurately, matches a novel structure against a library of domain structures to find the most similar ones. GRATH generates distributions of scores by comparing the novel domain against the different types of folds that have been classified previously in the CATH database of structural domains. GRATH uses a measure of similarity that details the geometric information, number of secondary structures and number of residues within secondary structures, that any two protein structures share. Although GRATH builds on well established approaches for secondary structure comparison, a novel scoring scheme has been introduced to allow ranking of any matches identified by the algorithm. More importantly, we have benchmarked the algorithm using a large dataset of 1702 non-redundant structures from the CATH database which have already been classified into fold groups, with manual validation. This has facilitated introduction of further constraints, optimization of parameters and identification of reliable thresholds for fold identification. Following these benchmarking trials, the correct fold can be identified with the top score with a frequency of 90%. It is identified within the ten most likely assignments with a frequency of 98%. GRATH has been implemented to use via a server (http://www.biochem.ucl.ac.uk/cgi-bin/cath/Grath.pl). GRATH's speed and accuracy means that it can be used as a reliable front-end filter for the more accurate, but computationally expensive, residue based structure comparison algorithm SSAP, currently used to classify domain structures in the CATH database. With an increasing number of structures being solved by the structural genomics initiatives, the GRATH server also provides an essential resource for determining whether newly determined structures are related to any known structures from which functional properties may be inferred.

Algorithms↗

Development of a high throughput screening assay for inhibitors of fibroblast growth factor-receptor-heparin interactions.

High throughput screening (HTS) of large compound libraries for inhibitors of growth factors raises the requirement for simple yet reliable assays. Fibroblast growth factors (FGFs) play a pivotal role in the multistep pathway of malignant transformation, tumor progression, metastasis, and angiogenesis. FGF-2 (basic FGF) requires a cooperative interaction with heparin or heparan sulfate proteoglycans in order to form functional growth factor-receptor complexes that are essential for receptor binding and activation. We have developed a simple screening system, devised to identify molecules that modulate heparin-FGF-receptor interactions. The system is composed of a heparin matrix, FGF-2, and a FGF receptor-1 protein engineered by genetically fusing the extracellular domain of FGF receptor-1 to alkaline phosphatase (FRAP). The screen is conducted using 96-well plates to which heparin has been covalently attached. FGF-2 is then bound to the plates through heparin-FGF interactions, followed by the addition of FRAP and compounds to be screened for modulation of heparin-FGF, receptor-heparin, and receptor-FGF interactions. The endpoint of the assay is measured enzymatically using the alkaline phosphatase (AP)-catalyzed formation of a chromogenic product, which is directly proportional to the amount of FRAP present on the plates as a heparin-FGF-FRAP ternary complex. Reduced AP values relative to control, as measured by spectrophotometry, indicate inhibition of the formation of an active FGF-receptor-heparin complex. The simple and versatile nature of the assay makes it an attractive HTS system. The screen has identified several potent inhibitors of FGF-2 receptor binding and activation. Furthermore, secondary screening of the HTS-recognized compounds identified several compounds that have the capacity to block growth factor-mediated tumor progression and angiogenesis in vivo.

Animals↗

An atlas of differential gene expression during early Xenopus embryogenesis.

We have carried out a large-scale, semi-automated whole-mount in situ hybridization screen of 8369 cDNA clones in Xenopus laevis embryos. We confirm that differential gene expression is prevalent during embryogenesis since 24% of the clones are expressed non-ubiquitously and 8% are organ or cell type specific marker genes. Sequence analysis and clustering yielded 723 unique genes displaying a differential expression pattern. Of these, 18% were already described in Xenopus, 47% have homologs and 35% are lacking significant sequence similarity in databases. Many of them encode known developmental regulators. We classified 363 of the 723 genes for which a Gene Ontology annotation for molecular function could be attributed and found 'DNA binding' and 'enzyme' the most represented terms. The most common protein domains encoded in these embryonic, differentially expressed genes are the homeobox and RNA Recognition Motif (RRM). Fifty-nine putative orthologs of human disease genes, and 254 organ or cell specific marker genes were identified. Markers were found for nasal placode and archenteron roof, organs for which a specific marker was previously unavailable. Markers were also found for novel subdomains of various other organs. The tissues for which most markers were found are muscle and epidermis. Expression of cell cycle regulators fell in two classes, containing proliferation-promoting and anti-proliferative genes, respectively. We identified 66 new members of the BMP4, chromatin, endoplasmic reticulum, and karyopherin synexpression groups, thus providing a first glimpse of their probable cellular roles. Cluster analysis of tissues to measure tissue relatedness yielded some unorthodox affinities besides expectable lineage relationships. In conclusion, this study represents an atlas of gene expression patterns, which reveals embryonic regionalization, provides novel marker genes, and makes predictions about the functional role of unknown genes.

Animals↗

The measurement and monitoring of surgical adverse events.

BACKGROUND: Surgical adverse events contribute significantly to postoperative morbidity, yet the measurement and monitoring of events is often imprecise and of uncertain validity. Given the trend of decreasing length of hospital stay and the increase in use of innovative surgical techniques--particularly minimally invasive and endoscopic procedures--accurate measurement and monitoring of adverse events is crucial. OBJECTIVES: The aim of this methodological review was to identify a selection of common and potentially avoidable surgical adverse events and to assess whether they could be reliably and validly measured, to review methods for monitoring their occurrence and to identify examples of effective monitoring systems for selected events. This review is a comprehensive attempt to examine the quality of the definition, measurement, reporting and monitoring of selected events that are known to cause significant postoperative morbidity and mortality. METHODS - SELECTION OF SURGICAL ADVERSE EVENTS: Four adverse events were selected on the basis of their frequency of occurrence and likelihood of evidence of measurement and monitoring: (1) surgical wound infection; (2) anastomotic leak; (3) deep vein thrombosis (DVT); (4) surgical mortality. Surgical wound infection and DVT are common events that cause significant postoperative morbidity. Anastomotic leak is a less common event, but risk of fatality is associated with delay in recognition, detection and investigation. Surgical mortality was selected because of the effort known to have been invested in developing systems for monitoring surgical death, both in the UK and internationally. Systems for monitoring surgical wound infection were also included in the review. METHODS - LITERATURE SEARCH: Thirty separate, systematic literature searches of core health and biomedical bibliographic databases (MEDLINE, EMBASE, CINAHL, HealthSTAR and the Cochrane Library) were conducted. The reference lists of retrieved articles were reviewed to locate additional articles. A matrix was developed whereby different literature and study designs were reviewed for each of the surgical adverse events. Each article eligible for inclusion was independently reviewed by two assessors. METHODS - CRITICAL APPRAISAL: Studies were appraised according to predetermined assessment criteria. Definitions and grading scales were assessed for: content, criterion and construct validity; repeatability; reproducibility; and practicality (surgical wound infection and anastomotic leak). Monitoring systems for surgical wound infection and surgical mortality were assessed on the following criteria: (1) coverage of the system; (2) whether or not denominator data were collected; (3) whether standard and agreed definitions were used; (4) inclusion of risk adjustment; (5) issues related to data collection; (6) postdischarge surveillance; (7) output in terms of feedback and wider dissemination. RESULTS - SURGICAL WOUND INFECTION: A total of 41 different definitions and 13 grading scales of surgical wound infection were identified from 82 studies. Definitions of surgical wound infection varied from presence of pus to complex definitions such as those proposed by the Centres for Disease Control in the USA. A small body of literature has been published on the content, criterion and construct validity of different definitions, and comparisons have been made against wound assessment scales and multidimensional indices. There are examples of comprehensive hospital-based monitoring systems of surgical wound infection, mainly under the auspices of nosocomial surveillance. To date, however, there is little evidence of systematic measurement and monitoring of surgical wound infection after hospital discharge. RESULTS - ANASTOMOTIC LEAK: Over 40 definitions of anastomotic leak were extracted from 107 studies of upper gastrointestinal, hepatopancreaticobiliary and lower gastrointestinal surgery. No formal evaluations were found that assessed the validity or reliability of definitions or severity scales of anastomotic leak. One definition was proposed during a national consensus workshop, but no evidence of its use was found in the surgical literature. The lack of a single definition or gold standard hampers comparison of postoperative anastomotic leak rates between studies and institutions. RESULTS - DEEP VEIN THROMBOSIS: Although a critical review of the DVT literature could not be completed within the realms of this review, it was evident that a number of new techniques for the detection and diagnosis of DVT have emerged in the last 20 years. The group recommends a separate review be undertaken of the different diagnostic tests to detect DVT. RESULTS - SURGICAL MORTALITY MONITORING SYSTEMS: The definition of surgical mortality is relatively consistent between monitoring systems, but duration of follow-up of death postdischarge varies considerably. The majority of systems report in-hospital mortality rates; only some have the potential to link deaths to national death registers. Risk assessment is an important factor and there should be a distinction between recording pre-intervention factors and postoperative complications. A variety of risk scoring systems was identified in the review. Factors associated with accurate and complete data collection include the employment of local, dedicated personnel, simple and structured prompts to ensure that clinical input is complete, and accurate and automated data capture and transfer. CONCLUSIONS: The use of standardised, valid and reliable definitions is fundamental to the accurate measurement and monitoring of surgical adverse events. This review found inconsistency in the quality of reporting of postoperative adverse events, limiting accurate comparison of rates over time and between institutions. The duration of follow-up for individual events will vary according to their natural history and epidemiology. Although risk-adjusted aggregated rates can act as screening or warning systems for adverse events, attribution of whether events are avoidable or preventable will invariably require further investigation at the level of the individual, unit or department. CONCLUSIONS - RECOMMENDATIONS FOR RESEARCH: (1) A single, standard definition of surgical wound infection is needed so that comparisons over time and between departments and institutions are valid, accurate and useful. Surgeons and other healthcare professionals should consider adopting the 1992 Centers for Disease Control (CDC) definition for superficial incisional, deep incisional and organ/space surgical site infection for hospital monitoring programmes and surgical audits. There is a need for further methodological research into the performance of the CDC definition in the UK setting. (2) There is a need to formally assess the reliability of self-diagnosis of surgical wound infection by patients. (3) There is a need to assess formally the reliability of case ascertainment by infection control staff. (4) Work is needed to create and agree a standard, valid and reliable definition of anastomotic leak which is acceptable to surgeons. (5) A systematic review is needed of the different diagnostic tests for the diagnosis of DVT. (6) The following variables should be considered in any future DVT review: anatomical region (lower limb, upper limb, pelvis); patient presentation (symptomatic, asymptomatic); outcome of diagnostic test (successfully completed, inconclusive, technically inadequate, negative); length of follow-up; cost of test; whether or not serial screening was conducted; and recording of laboratory cut-off values for fibrinogen equivalent units. (7) A critical review is needed of the surgical risk scoring used in monitoring systems. (8) In the absence of automated linkage there is a need to explore the benefits and costs of monitoring in primary care. (9) The growing potential for automated linkage of data from different sources (including primary care, the private sector and death registers) needs to be explored as a means of improving the ascertainment of surgical complications, including death. This linkage needs to be within the terms of data protection, privacy and human rights legislation. (10) A review is needed of the extent of the use and efficiency of routine hospital data versus special collections or voluntary reporting.

Humans↗

A scale space approach for automatically segmenting words from historical handwritten documents.

Many libraries, museums, and other organizations contain large collections of handwritten historical documents, for example, the papers of early presidents like George Washington at the Library of Congress. The first step in providing recognition/ retrieval tools is to automatically segment handwritten pages into words. State of the art segmentation techniques like the gap metrics algorithm have been mostly developed and tested on highly constrained documents like bank checks and postal addresses. There has been little work on full handwritten pages and this work has usually involved testing on clean artificial documents created for the purpose of research. Historical manuscript images, on the other hand, contain a great deal of noise and are much more challenging. Here, a novel scale space algorithm for automatically segmenting handwritten (historical) documents into words is described. First, the page is cleaned to remove margins. This is followed by a gray-level projection profile algorithm for finding lines in images. Each line image is then filtered with an anisotropic Laplacian at several scales. This procedure produces blobs which correspond to portions of characters at small scales and to words at larger scales. Crucial to the algorithm is scale selection, that is, finding the optimum scale at which blobs correspond to words. This is done by finding the maximum over scale of the extent or area of the blobs. This scale maximum is estimated using three different approaches. The blobs recovered at the optimum scale are then bounded with a rectangular box to recover the words. A postprocessing filtering step is performed to eliminate boxes of unusual size which are unlikely to correspond to words. The approach is tested on a number of different data sets and it is shown that, on 100 sampled documents from the George Washington corpus of handwritten document images, a total error rate of 17 percent is observed. The technique outperforms a state-of-the-art gap metrics word-segmentation algorithm on this collection.

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