Brainpeps: the blood–brain barrier peptide database

Peptides are able to cross the blood-brain barrier (BBB) through various mechanisms, opening new diagnostic and therapeutic avenues. However, their BBB transport data are scattered in the literature over different disciplines, using different methodologies reporting different influx or efflux aspects. Therefore, a comprehensive BBB peptide database (Brainpeps) was constructed to collect the BBB data available in the literature. Brainpeps currently contains BBB transport information with positive as well as negative results. The database is a useful tool to prioritize peptide choices for evaluating different BBB responses or studying quantitative structure-property (BBB behaviour) relationships of peptides. Because a multitude of methods have been used to assess the BBB behaviour of compounds, we classified these methods and their responses. Moreover, the relationships between the different BBB transport methods have been clarified and visualized.     

How many plans are needed in an IMRT multi-objective plan database?

In multi-objective radiotherapy planning, we are interested in Pareto surfaces of dimensions 2 up to about 10 (for head and neck cases, the number of structures to trade off can be this large). A key question that has not been answered yet is: how many plans does it take to sufficiently represent a high-dimensional Pareto surface? In this paper, we present a method to answer this question, and we show that the number of points needed is modest: 75 plans always controlled the error to within 5%, and in all cases but one, N + 1 plans, where N is the number of objectives, was enough for <15% error. We introduce objective correlation matrices and principal component analysis (PCA) of the beamlet solutions as two methods to understand this. PCA reveals that the feasible beamlet solutions of a Pareto database lie in a narrow, small dimensional subregion of the full beamlet space, which helps explain why the number of plans needed to characterize the database is small.     

Molecular mimicry reflected through database screening: serendipity or survival strategy?

Protein databases have been growing fast, and there has been considerable improvement in the computer software used to explore them. Subsequently, database screening commonly yields evidence of molecular mimicry between unrelated proteins. Here, Chantal Roudier and colleagues analyse the statistical significance of such sequence identities.     

IL2RGbase: a database of γc-chain defects causing human X-SCID

X-linked severe combined immunodeficiency (X-SCID) is an immune disorder caused by mutations in the X-linked gene IL2RG, which encodes the common γ chain of the lymphocyte receptors for interleukin 2 (IL-2) and many other cytokines. A database of human X-SCID mutations (IL2RGbase) has been assembled, and this article summarizes the first 136 entries from unrelated patients.     

Cancer incidence in primary Sjögren's syndrome: Data from the French hospitalization database

The relationship between cancer and primary Sjögren's syndrome (pSS) is uncertain. While the increased risk of hematological malignancies is well-known, data on the comparative incidence of solid neoplasms is conflicting. This study aimed to explore the associations between cancer and pSS. This nationwide population-based retrospective study from the French health insurance database (PMSI) evaluated patients hospitalized with new-onset pSS from 2011 to 2018 against age- and sex-matched hospitalized controls (1:10). The incidence of hematological malignancies and solid neoplasms was compared between the two groups. Mortality and multiple cancer incidence were also evaluated. Adjusted Hazard Ratios (aHR) calculations included confounding factors, such as low socioeconomic status. Among 25,661 hospitalized patients with pSS versus 252,543 matched patients (median follow-up of 3.96 years), we observed a higher incidence rate of lymphomas (aHR, 1.97 [95% CI, 1.59–2.43]), Waldenström macroglobulinemia (aHR, 10.8 [6.5–18.0]), and leukemia (aHR, 1.61 [1.1–2.4]). Thyroid cancer incidence was higher (aHR, 1.7 [1.1–2.8]), whereas bladder and breast cancer incidences were lower (aHR, 0.58 [0.37–0.89] and 0.60 [0.49–0.74], respectively). pSS patients with breast cancer exhibited a lower mortality rate. A limitation was that the database only encompasses hospitalized patients, and immunological and histological details are not listed. We confirmed the increased risk of hematological malignancies and thyroid cancers among patients with pSS. The lower risk of breast cancer suggests a role of hormonal factors and raises questions of the concept of immune surveillance within breast tissue. Epidemiological and translational studies are required to elucidate the relationships between pSS and cancer.     

Share and enjoy: anatomical models database—generating and sharing cardiovascular model data using web services

Sharing data between scientists and with clinicians in cardiac research has been facilitated significantly by the use of web technologies. The potential of this technology has meant that information sharing has been routinely promoted through databases that have encouraged stakeholder participation in communities around these services. In this paper we discuss the Anatomical Model Database (AMDB) (Gianni et al. Functional imaging and modeling of the heart. Springer, Heidelberg, 2009; Gianni et al. Phil Trans Ser A Math Phys Eng Sci 368:3039–3056, 2010) which both facilitate a database-centric approach to collaboration, and also extends this framework with new capabilities for creating new mesh data. AMDB currently stores cardiac geometric models described in Gianni et al. (Functional imaging and modelling of the heart. Springer, Heidelberg, 2009), a number of additional cardiac models describing geometry and functional properties, and most recently models generated using a web service. The functional models represent data from simulations in geometric form, such as electrophysiology or mechanics, many of which are present in AMDB as part of a benchmark study. Finally, the heartgen service has been added for producing left or bi-ventricle models derived from binary image data using the methods described in Lamata et al. (Med Image Anal 15:801–813, 2011). The results can optionally be hosted on AMDB alongside other community-provided anatomical models. AMDB is, therefore, a unique database storing geometric data (rather than abstract models or image data) combined with a powerful web service for generating new geometric models.     

Corpus callosum shape changes in early Alzheimer’s disease: an MRI study using the OASIS brain database

The corpus callosum (CC) is the largest fiber bundle connecting the left and right cerebral hemispheres. It has been a region examined extensively for indications of various pathologies, including Alzheimer’s disease (AD). Almost all previous studies of the CC in AD have been concerned with its size, particularly its mid-sagittal cross-sectional area (CCA). In this study, we show that the CC shape, characterized by its circularity (CIR), may be affected more profoundly than its size in early AD. MRI scans (n = 196) were obtained from the publicly available Open Access Series of Imaging Studies database. The CC cross-sectional region on the mid-sagittal section of the brain was automatically segmented using a novel algorithm. The CCA and CIR were compared in 98 normal controls (NC) subjects, 70 patients with very mild AD (AD-VM), and 28 patients with mild AD (AD-M). Statistical analysis of covariance controlling for age and intracranial capacity showed that both the CIR and the CCA were significantly reduced in the AD-VM group relative to the NC group (CIR: p = 0.004; CCA: p = 0.005). However, only the CIR was significantly different between the AD-M and AD-VM groups (p = 0.006) being smaller in the former. The CCA was not significantly different between the AD-M and AD-VM groups. The results suggest that CC shape may be a more sensitive marker than its size for monitoring the progression of AD. In order to facilitate independent analyses, the CC segmentations and the CCA and CIR data used in this study have been made publicly available (http://www.nitrc.org/projects/art).     

Heart＇omicsin＇AGEing （HOMAGE）：design,research objectives and characteristics of the common database

Heart failure is common in older people and its prevalence is increasing.The Heart ＇omics＇ in AGEing（HOMAGE） project aims to provide a biomarker approach that will improve the early diagnosis of heart failure.A large clinical database,based on（1） prospective population studies or（2） cross-sectional,prospective studies or randomized controlled trials（RCTs） of patients at risk for or with overt cardiovascular disease will be constructed to determine most promising ＇omics＇-based biomarkers to identify the risk of developing heart failure and/or comorbidities.Population studies,patient cohorts and RCTs are eligible for inclusion in the common database,if they received ethical approval to obtain and share data and have baseline information on cardiovascular risk factors.Currently,the HOMAGE database includes 43,065 subjects,from 20 studies in eight European countries,including healthy subjects from three population studies in France,Belgium and Italy（n = 7,124）,patients with heart failure（n = 4,312） from four cohorts in the UK,Spain and Switzerland and patients at high risk for cardiovascular disease（n = 31,629） in 13 cohorts.It is anticipated that more partners will join the consortium and enlarge the pooled data.This large merged database will be a useful resource with which to identify candidate biomarkers that play a role in the mechanism underlying the onset and progression of heart failure.     

ThalInd, a β-thalassemia and hemoglobinopathies database for India: defining a model country-specific and disease-centric bioinformatics resource

Web-based informatics resources for genetic disorders have evolved from genome-wide databases like OMIM and HGMD to Locus Specific databases (LSDBs) and National and Ethnic Mutation Databases (NEMDBs). However, with the increasing amenability of genetic disorders to diagnosis and better management, many previously underreported conditions are emerging as disorders of public health significance. In turn, the greater emphasis on noncommunicable disorders has generated a demand for comprehensive and relevant disease-based information from end-users, including clinicians, patients, genetic epidemiologists, health administrators and policymakers. To accommodate these demands, country-specific and disease-centric resources are required to complement the existing LSDBs and NEMDBs. Currently available preconfigured Web-based software applications can be customized for this purpose. The present article describes the formulation and construction of a Web-based informatics resource for β-thalassemia and other hemoglobinopathies, initially for use in India, a multiethnic, multireligious country with a population approaching 1,200 million. The resource ThalInd (http://ccg.murdoch.edu.au/thalind) has been created using the LOVD system, an open source platform-independent database system. The system has been customized to incorporate and accommodate data pertinent to molecular genetics, population genetics, genotype-phenotype correlations, disease burden, and infrastructural assessment. Importantly, the resource also has been aligned with the administrative health system and demographic resources of the country.     

Fabry-database.org: database of the clinical phenotypes, genotypes and mutant α-galactosidase A structures in Fabry disease

Fabry disease is a genetic disorder caused by a deficiency of α-galactosidase A (GLA). In our previous studies, we structurally investigated Fabry disease using a structural analysis system, and revealed that structural changes in GLA are very important for understanding the molecular basis of this disease. To the best of our knowledge, there is no database including the structures of mutant GLAs. Herein, we constructed a database of clinical phenotypes, genotypes and structures of mutant GLAs. This database can be accessed as 'fabry-database.org', and is user friendly, being equipped with powerful computational tools. This database will help researchers and clinicians who study Fabry disease.     

Assessing the predictive value of HIV indicator conditions in general practice: a case–control study using the THIN database

Background

UK HIV guidelines identify 37 clinical indicator conditions for adult HIV infection that should prompt an HIV test. However, few data currently exist to show their predictive value in identifying undiagnosed HIV.

Aim

To identify symptoms and clinical diagnoses associated with HIV infection and assess their relative importance in identifying HIV cases, using data from The Health Improvement Network (THIN) general practice database.

Design and setting

A case–control study in primary care.

Method

Cases (HIV-positive patients) were matched to controls (not known to have HIV). Data from 939 cases and 2576 controls were included (n = 3515). Statistical analysis assessed the incidence of the 37 clinical conditions in cases and controls, and their predictive value in indicating HIV infection, and derived odds ratios (ORs) for each indicator condition.

Results

Twelve indicator conditions were significantly associated with HIV infection; 74.2% of HIV cases (n = 697) presented with none of the HIV indicator conditions prior to diagnosis. The conditions most strongly associated with HIV infection were bacterial pneumonia (OR = 47.7; 95% confidence interval [CI] = 5.6 to 404.2) and oral candidiasis (OR = 29.4; 95% CI = 6.9 to 125.5). The signs and symptoms most associated with HIV were weight loss (OR = 13.4; 95% CI = 5.0 to 36.0), pyrexia of unknown origin (OR = 7.2; 95% CI = 2.8 to 18.7), and diarrhoea (one or two consultations).

Conclusion

This is the first study to quantify the predictive value of clinical diagnoses related to HIV infection in primary care. In identifying the conditions most strongly associated with HIV, this study could aid GPs in offering targeted HIV testing to those at highest risk.     

Predicting the risk of chronic kidney disease in the UK: an evaluation of QKidney? scores using a primary care database

Background

Chronic kidney disease is a major health concern that, if left untreated, may progress to end-stage kidney failure (ESKF). Identifying individuals at an increased risk of kidney disease and who might benefit from a therapeutic or preventive intervention is an important challenge.

Aim

To evaluate the performance of the QKidney® scores for predicting 5-year risk of developing moderate-severe kidney disease and ESKF in an independent UK cohort of patients from general practice records.

Design and setting

Prospective cohort study to evaluate the performance of two risk scores for kidney disease in 364 practices from the UK, contributing to The Health Improvement Network (THIN) database.

Method

Data were obtained from 1.6 million patients registered with a general practice surgery between 1 January 2002 and 1 July 2008, aged 35–74 years, with 43 186 incident cases of moderate-severe kidney disease and 2663 incident cases of ESKF. This is the first recorded evidence of moderate-severe chronic kidney and ESKF as recorded in general practice records.

Results

The results from this independent and external validation of QKidney scores indicate that both scores showed good performance data for both moderate-severe kidney disease and ESKF, on a large cohort of general practice patients. Discrimination and calibration statistics were better for models including serum creatinine; however, there were considerable amounts of missing data for serum creatinine. QKidney scores both with and without serum creatinine were well calibrated.

Conclusion

QKidney scores have been shown to be useful tools to predict the 5-year risk of moderate-severe kidney disease and ESKF in the UK.     

Development of a database for the rapid and accurate routine identification of Achromobacter species by matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry (MALDI-TOF MS)

ObjectivesAchromobacter spp. are emerging pathogens in respiratory samples from cystic fibrosis patients. The current reference methods (nrdA-sequencing or multilocus sequence typing) can identify 18 species which are often misidentified by conventional techniques as A. xylosoxidans. A few studies have suggested that matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry (MALDI-TOF/MS) provides accurate identification of the genus but not of species. The aims of this study were (a) to generate a database for MALDI-TOF/MS Bruker including the 18 species, (b) to evaluate the suitability of the database for routine laboratory identification, and (c) to compare its performance with that of the currently available Bruker default database.MethodsA total of 205 isolates belonging to the 18 species identified by nrdA sequencing were used to build a local database. Main spectra profiles (MSPs) were created according to Bruker's recommendations for each isolate with the Biotyper software. Performance of the default Bruker database and ours for routine use were compared by testing 167 strains (including 38 isolates used from MSP creation) belonging to the 18 species identified by nrdA sequencing directly from colonies cultivated on various media.ResultsOur new database accurately identified 99.4% (166/167) of the isolates from the 18 species (score ≥2.0) versus only 50.9% (85/167) with the Bruker database. In the Bruker database 17.3% of the isolates (29/167) were incorrectly identified as another species despite a score of ≥2.0.ConclusionsThe use of MALDI-TOF/MS in combination with a database developed with samples from 18 Achromobacter species provides rapid and accurate identification. This tool could be used to help future clinical studies.     

Epidemiology and evolution of antibiotic resistance of Haemophilus influenzae in children 5?years of age or less in France, 2001–2008: a retrospective database analysis

Trends in the evolution of antimicrobial resistance and mechanisms of resistance of Haemophilus influenzae to β-lactam antibiotics in France were assessed through a retrospective database review. The antimicrobial resistance of 2,206?H. influenzae strains from children aged ≤5 years was studied between 2001 and 2008. Strains were isolated from blood or cerebrospinal fluid (n?=?170), bronchial secretions (n?=?188), middle ear fluid, and nasopharynx or conjunctiva (n?=?1,848). A proportion of 95.1?% (n?=?2,097) were non-typeable H. influenzae (NTHi). β-lactamase production was identified in 27.5?% of NTHi isolates (all TEM-1), while β-lactamase-negative ampicillin resistance and β-lactamase-negative amoxicillin-clavulanate resistance among NTHi was 16.9 and 6.4?%, respectively. Over time, a statistically significant decrease in β-lactamase-producing strain prevalence (p?相似文献