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PubMed2004

iProLINK: an integrated protein resource for literature mining.

The exponential growth of large-scale molecular sequence data and of the PubMed scientific literature has prompted active research in biological literature mining and information extraction to facilitate genome/proteome annotation and improve the quality of biological databases. Motivated by the promise of text mining methodologies, but at the same time, the lack of adequate curated data for training and benchmarking, the Protein Information Resource (PIR) has developed a resource for protein literature mining--iProLINK (integrated Protein Literature INformation and Knowledge). As PIR focuses its effort on the curation of the UniProt protein sequence database, the goal of iProLINK is to provide curated data sources that can be utilized for text mining research in the areas of bibliography mapping, annotation extraction, protein named entity recognition, and protein ontology development. The data sources for bibliography mapping and annotation extraction include mapped citations (PubMed ID to protein entry and feature line mapping) and annotation-tagged literature corpora. The latter includes several hundred abstracts and full-text articles tagged with experimentally validated post-translational modifications (PTMs) annotated in the PIR protein sequence database. The data sources for entity recognition and ontology development include a protein name dictionary, word token dictionaries, protein name-tagged literature corpora along with tagging guidelines, as well as a protein ontology based on PIRSF protein family names. iProLINK is freely accessible at http://pir.georgetown.edu/iprolink, with hypertext links for all downloadable files.

Computational Biology↗
PubMed2006

Effectiveness of stereotactic radiosurgery alone or in combination with whole brain radiotherapy compared to conventional surgery and/or whole brain radiotherapy for the treatment of one or more brain metastases: a systematic review and meta-analysis.

PURPOSE: To assess the effectiveness of SRS alone or in combination with WBRT compared to surgery and/or WBRT in prolonging survival and improving the quality-of-life and functional status of patients with brain metastases. METHODS AND MATERIALS: A meta-analysis of randomized controlled trials and concurrent cohort studies examining SRS versus SRS + WBRT, SRS versus WBRT +/- surgical resection, SRS versus surgical resection only, or SRS + WBRT versus WBRT was conducted. Trial registers, bibliographic databases, and reference lists from selected studies and recent issues of relevant journals were searched. Neuro-oncology specialists were also contacted. All studies were analyzed independently by two reviewers, applying validated critical appraisal techniques. RESULTS: The review identified three RCTs and one cohort study. Among patients with multiple metastases, no difference in survival between those treated with WBRT + SRS and those treated with WBRT was found. However, in patients with one metastasis, a statistically significant difference, favoring those treated with WBRT + SRS, was observed. Regarding local tumor control at 24 months, rates were significantly higher in the WBRT + SRS treatment arm, regardless of the number of metastases. CONCLUSIONS: Adding SRS to WBRT improves survival in patients with one brain metastasis. Combining SRS and WBRT improves local tumour control and functional independence in all patients.

Brain Neoplasms↗
PubMed2026

Long-term consequences of childhood sexual abuse: An umbrella review of diagnostic meta-analyses.

BACKGROUND: Childhood sexual abuse (CSA) is a public health issue with an estimated worldwide prevalence of 12.7%, potentially leading to a host of lifelong and significant mental, physical, and behavioral health. The aim of this study was to comprehensively map the long-term consequences of childhood sexual abuse on physical, psychiatric, and behavioral health outcomes. METHODS: An umbrella review of meta-analyses of observational studies, registered on PROSPERO, was conducted to examine the diverse repercussions of childhood sexual abuse on adult health. Three bibliographic databases (PsycINFO, PubMed and Scopus) were searched from the inception of the respective databases to November 1st, 2022. Thirty-eight meta-analyses representing about 20 million individuals were analyzed, revealing a range of long-lasting consequences associated with CSA. RESULTS: Among physical pathologies, cervical cancer and functional neurological syndromes emerged as the most prominent, exhibiting significantly elevated odds ratios (ORs) of 4.18 IC95% and 3.30 IC95%, respectively. Sleep disorders and borderline personality disorders were the most prevalent mental health disorders associated with CSA, with respective ORs of 16.17 IC95% and 5.96 IC95%. Early sexual initiation (OR=3.59 IC95%, sexual assault (OR=3.36 IC95%, and prostitution (OR=3.24 IC95%) emerged as the most common behavioral consequences. Notably, no significant differences in the consequences of CSA were observed between men and women, except for reproductive health outcomes. DISCUSSION: When faced with certain pathologies, clinicians should consider and discuss sexual abuse with their patients. The consequences of abuse have a multifactorial origin, which is a weakness, as are the problems of defining abuse. The strength of our study is that it lists the consequences published in high-quality studies. CONCLUSION: This umbrella review provides compelling evidence of the profound and far-reaching impact of childhood sexual abuse on a broad spectrum of physical, mental, and behavioral health issues.

Humans↗
PubMed2006

Fertility preservation in female cancer patients: current developments and future directions.

OBJECTIVE: To review the current advances in fertility preservation strategies and to discuss future directions with an emphasis on ovarian tissue cryobanking. DESIGN: The publications related to fertility preservation in cancer patients were identified through Medline and other bibliographic databases, focusing on the most recent developments. CONCLUSION(S): There are several options for fertility preservation in cancer patients. Even though most of them are still experimental and their efficacy and reliability have not been determined, the future of fertility preservation in women with cancer is promising. In particular, the recent report of a live birth after transplantation of human ovarian tissue has reinforced the clinical potential of ovarian tissue banking for fertility preservation. Many exciting studies are underway to improve the efficacy and solve the problems with current fertility preservation strategies. It is inevitable that we will see the emergence of more complex ethical problems with the application of new technologies to humans. However, continuous efforts to improve current strategies and to develop new strategies will benefit many women and children who are facing premature ovarian failure and sterility.

Female↗
PubMed2006

Oocyte cryopreservation.

OBJECTIVE: To review historical and contemporary advances in oocyte-cryopreservation techniques and outcomes. DESIGN: Publications related to oocyte cryopreservation were identified through MEDLINE and other bibliographic databases. CONCLUSION(S): Oocyte cryopreservation can be used as an adjunct to conventional IVF and as an option for fertile women to electively cryopreserve their gametes. Recent reports indicate pregnancy rates comparable to those for cryopreserved embryos by either slow-freeze or vitrification methods. Larger prospective trials are needed to determine the true efficacy and safety of oocyte cryopreservation. Until a sufficient number of births is reached and adequate outcome data are collected, oocyte cryopreservation should continue to be considered experimental and to be performed under the oversight of an institutional review board.

Birth Rate↗
PubMed2005

Using literature-based discovery to identify disease candidate genes.

We present BITOLA, an interactive literature-based biomedical discovery support system. The goal of this system is to discover new, potentially meaningful relations between a given starting concept of interest and other concepts, by mining the bibliographic database MEDLINE. To make the system more suitable for disease candidate gene discovery and to decrease the number of candidate relations, we integrate background knowledge about the chromosomal location of the starting disease as well as the chromosomal location of the candidate genes from resources such as LocusLink and Human Genome Organization (HUGO). BITOLA can also be used as an alternative way of searching the MEDLINE database. The system is available at http://www.mf.uni-lj.si/bitola/.

Algorithms↗
PubMed2005

Impact of clinical information-retrieval technology on physicians: a literature review of quantitative, qualitative and mixed methods studies.

PURPOSE: This paper appraises empirical studies examining the impact of clinical information-retrieval technology on physicians and medical students. METHODS: The world literature was reviewed up to February 2004. Two reviewers independently identified studies by scrutinising 3368 and 3249 references from bibliographic databases. Additional studies were retrieved by hand searches, and by searching ISI Web of Science for citations of articles. Six hundred and five paper-based articles were assessed for relevance. Of those, 40 (6.6%) were independently appraised by two reviewers for relevance and methodological quality. These articles were quantitative, qualitative or of mixed methods, and 26 (4.3%) were retained for further analysis. For each retained article, two teams used content analysis to review extracted textual material (quantitative results and qualitative findings). RESULTS: Observational studies suggest that nearly one-third of searches using information-retrieval technology may have a positive impact on physicians. Two experimental and three laboratory studies do not reach consensus in support of a greater impact of this technology compared with other sources of information, notably printed educational material. Clinical information-retrieval technology may affect physicians, and further research is needed to examine its impact in everyday practice.

Attitude of Health Personnel↗
PubMed2006

The roles of policy and professionalism in the protection of processed clinical data: a literature review.

BACKGROUND: Routinely collected clinical data is increasingly used for health service management, audit, and research. Even apparently anonymised data are subject to data protection. The relevant principles were set out in a treaty of the Council of Europe and subsequent policy has been based on these. However, little has been written about implementing policy and the role of health informaticians in this process. OBJECTIVE: To define the elements of an effective implementation policy; the role of the health informatician in protecting processed clinical data. METHODS: We performed a literature review of bibliographic databases, a manual search of the major medical informatics associations' websites, relevant working groups and an affiliated journal. Fifty-four papers relevant to implementation were identified. RESULTS: The effective implementation of policy requires consideration of technical, organisational, personnel and professional issues. However, there is no clearly defined formula for successful implementation of data protection policy. CONCLUSIONS: Patients and professionals need a system they can trust, and processes that can be easily incorporated into everyday practice. The lack of a core generalisable theory or strong professional code in health informatics limits the ability of the health informaticians to implement policy.

Confidentiality↗
PubMed2005

Narrowband UVB phototherapy in skin conditions beyond psoriasis.

BACKGROUND: Narrowband (NB) UVB phototherapy has been proven to be clearly more effective than broadband UVB and safer and/or more practicable than psoralen-UVA in the management of psoriasis. However, the role of NB UVB seems to be less clear in the management of skin conditions beyond psoriasis. OBJECTIVES: We sought to give an update on clinical experiences in NB UVB of nonpsoriatic skin conditions, and to establish its current position within the spectrum of competing photo(chemo)therapeutic options. METHODS: The computerized bibliographic database PubMed, without time limits, and other sources were screened for clinical trials on NB UVB. Included were research articles of randomized controlled trials, open prospective studies, and retrospective observations on NB UVB in skin disorders other than psoriasis. RESULTS: A total of 28 articles met our eligibility criteria including 6 randomized controlled studies, 16 open prospective studies, and 6 retrospective observations. NB UVB is effective in patients with chronic atopic dermatitis (AD) (n = 719) and generalized vitiligo (n = 305) and appears to have some advantages over competing photo(chemo)therapeutic regimens. NB UVB also seems to be effective in patients with polymorphic light eruption (n = 25), early stages of cutaneous T-cell lymphoma (n = 108), chronic urticaria (n = 88), lichen planus (n = 15), pruritus associated with polycythemia vera (n = 10), seborrheic dermatitis (n = 18), actinic prurigo (n = 6), and acquired perforating dermatosis (n = 5). The quality of evidence determined for the aforementioned diagnoses ranged from high to moderate to very low. CONCLUSIONS: The best currently available data on NB UVB in nonpsoriatic conditions exist for AD and generalized vitiligo. In view of its efficacy, benefit/risk profile, and costs, NB UVB may be considered the first-line photo(chemo)therapeutic option for moderately severe AD and widespread vitiligo. In the treatment of most other nonpsoriatic conditions, NB UVB appears to be effective, but current data allow no definitive conclusions as to whether NB UVB should be preferred to competing photo(chemo)therapeutic options such as UVA1 and psoralen-UVA regimens. Because NB UVB may have a wider indication spectrum, including AD, vitiligo, and early-stage T-cell lymphoma, and appears to be equally effective or even more effective than broadband UVB, a switch from broadband UVB to NB UVB seems to be justified.

Dermatitis, Atopic↗
PubMed2005

A systematic review of school-based smoking prevention trials with long-term follow-up.

BACKGROUND: Several systematic reviews of school-based smoking prevention trials have shown short-term decreases in smoking prevalence but have not examined long-term follow-up evaluation. The purpose of this study was to conduct a systematic review of rigorously evaluated interventions for school-based smoking prevention with long-term follow-up data. METHODS: We searched online bibliographic databases and reference lists from review articles and selected studies. We included all school-based, randomized, controlled trials of smoking prevention with follow-up evaluation to age 18 or 12th grade and at least 1 year after intervention ended, and that had smoking prevalence as a primary outcome. The primary outcome was current smoking prevalence (defined as at least 1 cigarette in the past month). RESULTS: The abstracts or full-text articles of 177 relevant studies were examined, of which 8 met the selection criteria. The 8 articles included studies differing in intervention intensity, presence of booster sessions, follow-up periods, and attrition rates. Only one study showed decreased smoking prevalence in the intervention group. CONCLUSIONS: Few studies have evaluated the long-term impact of school-based smoking prevention programs rigorously. Among the 8 programs that have follow-up data to age 18 or 12th grade, we found little to no evidence of long-term effectiveness.

Adolescent↗
PubMed2004

Use of morphological analysis in protein name recognition.

Protein name recognition aims to detect each and every protein names appearing in a PubMed abstract. The task is not simple, as the graphic word boundary (space separator) assumed in conventional preprocessing does not necessarily coincide with the protein name boundary. Such boundary disagreement caused by tokenization ambiguity has usually been ignored in conventional preprocessing of general English. In this paper, we argue that boundary disagreement poses serious limitations in biomedical English text processing, not to mention protein name recognition. Our key idea for dealing with the boundary disagreement is to apply techniques used in Japanese morphological analysis where there are no word boundaries. Having evaluated the proposed method with GENIA corpus 3.02, we obtain F-measure of 69.01 on a strict criterion and 79.32 on a relaxed criterion. The result is comparable to other published work in protein name recognition, without resorting to manually prepared ad hoc feature engineering. Further, compared to the conventional preprocessing, the use of morphological analysis as preprocessing improves the performance of protein name recognition and reduces the execution time.

Abstracting and Indexing↗
PubMed2004

Using automatically learnt verb selectional preferences for classification of biomedical terms.

In this paper, we present an approach to term classification based on verb selectional patterns (VSPs), where such a pattern is defined as a set of semantic classes that could be used in combination with a given domain-specific verb. VSPs have been automatically learnt based on the information found in a corpus and an ontology in the biomedical domain. Prior to the learning phase, the corpus is terminologically processed: term recognition is performed by both looking up the dictionary of terms listed in the ontology and applying the C/NC-value method for on-the-fly term extraction. Subsequently, domain-specific verbs are automatically identified in the corpus based on the frequency of occurrence and the frequency of their co-occurrence with terms. VSPs are then learnt automatically for these verbs. Two machine learning approaches are presented. The first approach has been implemented as an iterative generalisation procedure based on a partial order relation induced by the domain-specific ontology. The second approach exploits the idea of genetic algorithms. Once the VSPs are acquired, they can be used to classify newly recognised terms co-occurring with domain-specific verbs. Given a term, the most frequently co-occurring domain-specific verb is selected. Its VSP is used to constrain the search space by focusing on potential classes of the given term. A nearest-neighbour approach is then applied to select a class from the constrained space of candidate classes. The most similar candidate class is predicted for the given term. The similarity measure used for this purpose combines contextual, lexical, and syntactic properties of terms.

Abstracting and Indexing↗
PubMed2004

Improving the performance of dictionary-based approaches in protein name recognition.

Dictionary-based protein name recognition is often a first step in extracting information from biomedical documents because it can provide ID information on recognized terms. However, dictionary-based approaches present two fundamental difficulties: (1) false recognition mainly caused by short names; (2) low recall due to spelling variations. In this paper, we tackle the former problem using machine learning to filter out false positives and present two alternative methods for alleviating the latter problem of spelling variations. The first is achieved by using approximate string searching, and the second by expanding the dictionary with a probabilistic variant generator, which we propose in this paper. Experimental results using the GENIA corpus revealed that filtering using a naive Bayes classifier greatly improved precision with only a slight loss of recall, resulting in 10.8% improvement in F-measure, and dictionary expansion with the variant generator gave further 1.6% improvement and achieved an F-measure of 66.6%.

Abstracting and Indexing↗
PubMed2004

Term identification in the biomedical literature.

Sophisticated information technologies are needed for effective data acquisition and integration from a growing body of the biomedical literature. Successful term identification is key to getting access to the stored literature information, as it is the terms (and their relationships) that convey knowledge across scientific articles. Due to the complexities of a dynamically changing biomedical terminology, term identification has been recognized as the current bottleneck in text mining, and--as a consequence--has become an important research topic both in natural language processing and biomedical communities. This article overviews state-of-the-art approaches in term identification. The process of identifying terms is analysed through three steps: term recognition, term classification, and term mapping. For each step, main approaches and general trends, along with the major problems, are discussed. By assessing previous work in context of the overall term identification process, the review also tries to delineate needs for future work in the field.

Abbreviations as Topic↗
PubMed2004

Enhancing performance of protein and gene name recognizers with filtering and integration strategies.

Named entity (NE) recognition is a fundamental task in biological relationship mining. This paper considers protein/gene collocates extracted from biological corpora as restrictions to enhance the precision rate of protein/gene name recognition. In addition, we integrate the results of multiple NE recognizers to improve the recall rates. Yapex and KeX, and ABGene and Idgene are taken as examples of protein and gene name recognizers, respectively. The precision of Yapex increases from 70.90 to 85.84% at the low expense of the recall rate (i.e., it only decreases 2.44%) when collocates are incorporated. When both filtering and integration strategies are employed together, the Yapex-based integration with KeX shows good performance, i.e., the F-score increases by 7.83% compared to the pure Yapex method. The results of gene recognition show the same tendency. The ABGene-based integration with Idgene shows a 10.18% F-score increase compared to the pure ABGene method. These successful methodologies can be easily extended to other name finders in biological documents.

Abstracting and Indexing↗
PubMed2004

Using name-internal and contextual features to classify biological terms.

There has been considerable work done recently in recognizing named entities in biomedical text. In this paper, we investigate the named entity classification task, an integral part of the named entity extraction task. We focus on the different sources of information that can be utilized for classification, and note the extent to which they are effective in classification. To classify a name, we consider features that appear within the name as well as nearby phrases. We also develop a new strategy based on the context of occurrence and show that they improve the performance of the classification system. We show how our work relates to previous works on named entity classification in the biological domain as well as to those in generic domains. The experiments were conducted on the GENIA corpus Ver. 3.0 developed at University of Tokyo. We achieve f value of 86 in 10-fold cross validation evaluation on this corpus.

Abstracting and Indexing↗
PubMed2004

Comparison of character-level and part of speech features for name recognition in biomedical texts.

The immense volume of data which is now available from experiments in molecular biology has led to an explosion in reported results most of which are available only in unstructured text format. For this reason there has been great interest in the task of text mining to aid in fact extraction, document screening, citation analysis, and linkage with large gene and gene-product databases. In particular there has been an intensive investigation into the named entity (NE) task as a core technology in all of these tasks which has been driven by the availability of high volume training sets such as the GENIA v3.02 corpus. Despite such large training sets accuracy for biology NE has proven to be consistently far below the high levels of performance in the news domain where F scores above 90 are commonly reported which can be considered near to human performance. We argue that it is crucial that more rigorous analysis of the factors that contribute to the model's performance be applied to discover where the underlying limitations are and what our future research direction should be. Our investigation in this paper reports on variations of two widely used feature types, part of speech (POS) tags and character-level orthographic features, and makes a comparison of how these variations influence performance. We base our experiments on a proven state-of-the-art model, support vector machines using a high quality subset of 100 annotated MEDLINE abstracts. Experiments reveal that the best performing features are orthographic features with F score of 72.6. Although the Brill tagger trained in-domain on the GENIA v3.02p POS corpus gives the best overall performance of any POS tagger, at an F score of 68.6, this is still significantly below the orthographic features. In combination these two features types appear to interfere with each other and degrade performance slightly to an F score of 72.3.

Abbreviations as Topic↗
PubMed2004

Gene name identification and normalization using a model organism database.

Biology has now become an information science, and researchers are increasingly dependent on expert-curated biological databases to organize the findings from the published literature. We report here on a series of experiments related to the application of natural language processing to aid in the curation process for FlyBase. We focused on listing the normalized form of genes and gene products discussed in an article. We broke this into two steps: gene mention tagging in text, followed by normalization of gene names. For gene mention tagging, we adopted a statistical approach. To provide training data, we were able to reverse engineer the gene lists from the associated articles and abstracts, to generate text labeled (imperfectly) with gene mentions. We then evaluated the quality of the noisy training data (precision of 78%, recall 88%) and the quality of the HMM tagger output trained on this noisy data (precision 78%, recall 71%). In order to generate normalized gene lists, we explored two approaches. First, we explored simple pattern matching based on synonym lists to obtain a high recall/low precision system (recall 95%, precision 2%). Using a series of filters, we were able to improve precision to 50% with a recall of 72% (balanced F-measure of 0.59). Our second approach combined the HMM gene mention tagger with various filters to remove ambiguous mentions; this approach achieved an F-measure of 0.72 (precision 88%, recall 61%). These experiments indicate that the lexical resources provided by FlyBase are complete enough to achieve high recall on the gene list task, and that normalization requires accurate disambiguation; different strategies for tagging and normalization trade off recall for precision.

Abstracting and Indexing↗