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Vitamin B 12 deficiency is rare in the paediatric population. The most common cause is a diet low in animal products. Particularly at risk are infants exclusively breast-fed by mothers with hypovitaminosis B 12 . Much rarer causes include disorders of cobalamin absorption, transport or metabolism. There are mainly haematological, neurological and gastrointestinal symptoms. Diagnostic tests should include complete blood count with differential, including the MCV and RDW, the concentration of ferritin, folic acid and cobalamin in the serum and plasma homocysteine, and methylmalonic acid excretion in urine. We present the case of 10-month-old girl breast fed, admitted to the Paediatric Department due to inhibition of weight gain and developmental delay. Among the first symptoms of vitamin B 12 deficiency, which occurred in the child 6 months of age, was refusal to solid food. Increased MCV and RDW with normal haemoglobin values were observed in blood counts performed in 7 months of age. During hospitalization we noticed significantly elevated plasma homocysteine levels and a very large excretion of methylmalonic acid in the urine, which quickly normalized after the start of treatment with cyanocobalamin. At the beginning of therapy the benign myoclonic jerks occurred, which resolved spontaneously after a few days. Regression of neurological symptoms was not fully satisfactory. Lack of acceptance of foods other than breast milk can be one of the first signs of vitamin B 12 deficiency in infants and contribute to the severity of the deficit.

Sensing of cytosolic nucleotides is a critical initial step in the elaboration of type I interferon. One of several upstream receptor cGAS (cyclic-GMP-AMP synthase) binds to cytosolic DNA and generates di-cyclic nucleotides that act as secondary messengers. These secondary messengers bind directly to Stimulator of Interferon Genes (STING). STING recruits TANK binding kinase 1 (TBK1) which acts as a critical node that allows for efficient activation of interferon regulatory factors (IRFs) to drive the anti-viral transcriptome. NLRC3 is a recently characterized nucleotide-binding domain, leucine rich repeat containing protein (NLR) that negatively regulates the type I interferon pathway by inhibiting subcellular redistribution and effective signaling of STING, thus blunting the transcription of type I interferons. NLRC3 is predominantly expressed in lymphoid and myeloid cells. IQGAP1 was identified as a putative interacting partner of NLRC3 through yeast two hybrid screening. Here we show that a novel ER-resident protein associates with NLRC3 in human cells. This interaction occurs at the ER. This data provides a mechanism by which NLRC3 localizes to the ER to affect STING signaling in response to cytosolic nucleotides.

Plastic multilayers are widely used for baby food packaging. However, it is important to consider that migration of food contact materials (FCM) into the baby food can occur. The comprehensive identification of potential migrants, including intentionally added substances (IAS) and non-intentionally added substances (NIAS), is required to assess the safety of these packaging materials. In this study, high resolution accurate mass spectrometry (HRAMS) with a data-independent acquisition method of sequential mass windows enables the detection of substances with corresponding deconvoluted fragment mass spectra. The identification of unexpected migrants present in the food simulants and in real baby food was facilitated by filtering strategies and by an in-house library. This approach has allowed the identification of 42 migrants, including eight NIAS detected for the first time. Two oligomers were quantified by means of reference standard materials at concentration levels above 0.010 mg/kg, exceeding the maximum residue levels for baby food.

An ion mobility quadrupole time-of-flight mass spectrometry-based pesticide suspect screening methodology was developed and validated covering 20 plant-derived food matrices deriving from six commodity groups of different complexity according to the actual European Commission document SANTE/11813/2017 applying a QuEChERS sample preparation protocol. The method combines ultra-performance liquid chromatography, traveling wave ion mobility, and quadrupole time-of-flight mass spectrometry. Besides the determination of the physicochemical property collision cross-section and the establishment of a corresponding scientific suspect screening database comprising 280 pesticides for several pesticides, different protomers, sodium adducts, as well as dimers were identified in ion mobility spectrometry traces. Additionally, collision cross-section values were included in the validation requirements regarding chromatography and mass spectrometry for the detection of pesticides. A collision cross-section value window was analyzed within a tolerable error of ±2%. For this cross-matrix validation, screening detection limits were determined at concentration levels of 0.100 mg/kg (84% of the original pesticide scope), 0.010 mg/kg (56%), and 0.001 mg/kg (21%). By application of ion mobility spectrometry, the compound identification was improved due to independence of commodity of concern and concentration levels of analyte molecules, as false assignments are reduced by application of a collision cross-section range.

Septic shock may be complicated by a state of immune suppression, with ominous prognosis significance. Although the underlying pathophysiological mechanisms are poorly understood, it is possible that norepinephrine, used to treat circulatory failure during septic shock, plays a significant contributing role. Indeed, besides its hemodynamic effects, norepinephrine exerts multiple immunosuppressive actions, which are primarily mediated by beta-2 adrenergic receptors expressed by immune cells. Furthermore, norepinephrine has the ability to promote the growth of numerous bacteria, and could thereby foster the development of nosocomial infections. Norepinephrine being one of the most prescribed drugs in intensive care medicine, knowledge of these particular immunological effects is essential for the intensive care physicians.Le choc septique peut se compliquer, à distance de l’épisode aigu, d’un état d’immunosuppression grevé d’une morbi-mortalité élevée. Bien que l’on en ignore les mécanismes physiopathologiques, il est possible que la noradrénaline utilisée dans le traitement de la défaillance circulatoire du choc septique, joue un rôle contributif significatif. En effet, la noradrénaline possède, à côté de ses effets hémodynamiques, de multiples effets immunodépresseurs médiés par des récepteurs bêta-2 adrénergiques exprimés par les cellules immunes. De plus, la noradrénaline a la capacité de stimuler la croissance de la plupart des bactéries, pouvant favoriser la survenue d’infections nosocomiales. La noradrénaline étant l’un des médicaments les plus prescrits en réanimation, il est essentiel que ces effets particuliers soient connus des cliniciens.

Objective The trade-off between the speed and simplicity of dictionary-based term recognition and the richer linguistic information provided by more advanced natural language processing (NLP) is an area of active discussion in clinical informatics. In this paper, we quantify this trade-off among text processing systems that make different trade-offs between speed and linguistic understanding. We tested both types of systems in three clinical research tasks: phase IV safety profiling of a drug, learning adverse drug–drug interactions, and learning used-to-treat relationships between drugs and indications.Materials We first benchmarked the accuracy of the NCBO Annotator and REVEAL in a manually annotated, publically available dataset from the 2008 i2b2 Obesity Challenge. We then applied the NCBO Annotator and REVEAL to 9 million clinical notes from the Stanford Translational Research Integrated Database Environment (STRIDE) and used the resulting data for three research tasks.Results There is no significant difference between using the NCBO Annotator and REVEAL in the results of the three research tasks when using large datasets. In one subtask, REVEAL achieved higher sensitivity with smaller datasets.Conclusions For a variety of tasks, employing simple term recognition methods instead of advanced NLP methods results in little or no impact on accuracy when using large datasets. Simpler dictionary-based methods have the advantage of scaling well to very large datasets. Promoting the use of simple, dictionary-based methods for population level analyses can advance adoption of NLP in practice.

Presented is a retrospective outcome study of a 15-year single institutional experience with a contemporary cohort of patients with hypoplastic left heart syndrome and complex that underwent a “Giessen Hybrid” stage I as initial palliation. Hybrid approach consisting of surgical bilateral pulmonary artery banding and percutaneous duct stenting with or without atrial septum manipulation was developed from a rescue approach to a first-line procedure. Comprehensive Aristotle score defined pre-operative condition. Fifteen-year follow-up mortality is reported as occurring within the staged univentricular palliation or before and after biventricular repair. Hybrid stage I was performed in 154 patients; 107 should be treated by single ventricle palliation, 33 by biventricular repair (BVR), 7 received heart transplantation, and 7 were treated by comfort care, respectively. Overall 34 children died. The Aristotle score (mean value 18.2 ± 3) classified for univentricular circulations in newborns did not have statistical impact on the outcome. Two patients died during stage I (1.2 %), and the interstage I mortality was 6.7 %, and stage II mortality 9 %, respectively. Stage III was up to now performed in 57 patients without mortality. At 1 year, the overall unadjusted survival of HLHS and variants was 84 % and following BVR 89 %, respectively. The Fifteen-year survival rate for HLHS and variants was 77 %, with no significant impact of birth weight of less than 2.5 kg. In conclusion, Hybrid stage I fulfilled the criteria of life-saving approach. In our institution, Hybrid procedure replaced Norwood-staged palliation with a considerable mid- and long-term survival rate. Considering interstage mortality close surveillance is mandatory.

Background and objective Electronic health records (EHRs) are increasingly being used to complement the FDA Adverse Event Reporting System (FAERS) and to enable active pharmacovigilance. Over 30% of all adverse drug reactions are caused by drug–drug interactions (DDIs) and result in significant morbidity every year, making their early identification vital. We present an approach for identifying DDI signals directly from the textual portion of EHRs. Methods We recognize mentions of drug and event concepts from over 50 million clinical notes from two sites to create a timeline of concept mentions for each patient. We then use adjusted disproportionality ratios to identify significant drug–drug–event associations among 1165 drugs and 14 adverse events. To validate our results, we evaluate our performance on a gold standard of 1698 DDIs curated from existing knowledge bases, as well as with signaling DDI associations directly from FAERS using established methods. Results Our method achieves good performance, as measured by our gold standard (area under the receiver operator characteristic (ROC) curve >80%), on two independent EHR datasets and the performance is comparable to that of signaling DDIs from FAERS. We demonstrate the utility of our method for early detection of DDIs and for identifying alternatives for risky drug combinations. Finally, we publish a first of its kind database of population event rates among patients on drug combinations based on an EHR corpus. Conclusions It is feasible to identify DDI signals and estimate the rate of adverse events among patients on drug combinations, directly from clinical text; this could have utility in prioritizing drug interaction surveillance as well as in clinical decision support.

The high amount of industrial robots in body shop allows significant energy savings, e. g. by the use of appropriate robot sizes for certain applications or energy efficient types of robots. Based on an extensive cluster analysis of several body-in-white systems and with the development of a special reference trajectory a new resource has been established to compare robots of different sizes or fabricators. Building on these results decisions for the choice of robots can be made in production planning to reduce energy consumption by the use of energy efficient robots. Furthermore, the expected energy consumptions of a robot can be estimated in advance.

Sickle cell disease (SCD) is the most common genetic condition in the world and disproportionately affects African Americans in families with lower household incomes. SCD is characterized by a variety of complications including episodes of severe pain, chronic anemia, and end-organ damage. Morbidity from SCD begins in infancy and increases in frequency and severity with age. Complications during childhood and adolescence, both critical learning periods for youth, substantially impact educational attainment and life outcomes. SCD-related hospitalizations are associated with social determinants of health, such as socioeconomic status (SES), depression, health literacy, and educational outcomes. In youth with SCD, family and neighborhood SES are predictors of pain level, pain frequency, and overall quality of life. In addition to the physiological impacts of SCD, individuals with SCD experience emotional and stress related effects of the disease that may impact daily quality of life and frequency and severity of pain. Studies have found that hospital admission frequency has limited or no impact on academic outcomes in youth with SCD. Few studies have explicitly examined the relationship between SCD-related pain and educational, socioeconomic, and mental health outcomes. This is a cross-sectional study of patient survey data from a single site in the Sickle Cell Disease Implementation Science Consortium (SCDIC). The primary objective was to identify a relationship between educational attainment, employment status, mental health, and the frequency, severity, or length of pain crises for individuals with SCD. Multivariate analysis was used to assess the impact of patients' educational attainment, employment status, annual household income (low = less than $25,000, high = $75,001 and above), and self-reported depression on the frequency, length, and severity of SCD-related pain. Our central hypothesis was that individuals with a history of depression, lower educational attainment, periods of unemployment, and lower incomes experience more frequent, more severe, and longer pain crises. A total of 307 participants were included. The mean age was 27.4 years (range 15 to 45), 58.3% were female, and 99% were African American. Sixty-two percent had Hgb SS, the most severe form of SCD. About half of all patients (50.5%) reported they take pain medication every day for SCD and majority were on some form of disease modification (64.2% on hydroxyurea (HU), 20.2% on chronic blood transfusion). Slightly less than half (48.9%) reported their highest level of education as a high school diploma or lower. Most were unemployed (15.3%), students (22.8%), or disabled (21.5%), and 59.2% reported an average annual household income less than $25,000. Univariate analysis revealed statistically significant associations between employment status as unemployed or disabled and frequency of pain (p < .001), employment status as unemployed or disabled and severity of pain (p < .001), and employment status as disabled and length of pain > 4 days. Relationships between depression and frequency and severity of pain were statistically significant at the p < .001 level, and between depression and length of pain > 1 week at the p < .01 level. Multivariate analysis revealed positive statistically significant relationships between depression and high pain frequency (p < .001), employment status as disabled and severe pain (p < .01), depression and severe pain (p < .01), and employment status as disabled and length of pain >4 days (p < .05), Table 1. Educational attainment did not demonstrate statistically significant relationships with pain outcomes. No variables demonstrated statistically significant relationships with length of pain > 1 week and length of pain > 2 weeks. The only significant association with pain outcomes was that HU users were less likely to take daily opioids. Individuals with SCD who are disabled or have a history of depression are more likely to report more severe and frequent pain. No relationship emerged between educational attainment and pain outcomes. As the results are limited to the cross-sectional design, we cannot make statements of causality. For now, we know that people with SCD and these risk factors need further study for interventions. We plan to further assess study participants across all eight SCDIC sites in the next phase of this work. Disclosures King: Bioline: Consultancy; Amphivena Therapeutics: Research Funding; Incyte: Consultancy; Cell Works: Consultancy; Celgene: Consultancy; Magenta Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novimmune: Research Funding; RiverVest: Consultancy; Tioma Therapeutics (formerly Vasculox, Inc.):: Consultancy; WUGEN: Equity Ownership.

Background: Sickle cell disease (SCD) is a genetic hematologic condition affecting more than 300,000 individuals worldwide. Most of the 100,000 individuals with SCD in the United States are African-American. An estimated 50% of those with the most severe genotype of SCD (HbSS) will have an overt or silent cerebral infarct (SCI) by age 30. While a significant number of studies have addressed the cognitive function and brain imaging of children with SCD, very few have included adults. As disease modification has increased over the last decade, a modern assessment of adults with SCD is needed. The aims of this study are to: 1. Determine the prevalence of cognitive impairment in adults with SCD 2. Determine if adults with SCD have deficits in functional task performance skills 3. Assess if and how cognitive function and task performance change over time Methods: This is a cross-sectional analysis of a prospective, observational cohort study. Adults, 18 years of age or older, with any form of SCD were recruited from the SCD clinics at Washington University in St. Louis. During baseline testing, participants completed the Wechsler Abbreviated Scale of Intelligence (WASI-II), National Institutes of Health Toolbox Cognition Battery (NIHTB-CB), and the Medication subtest of the Executive Function Performance Test (EFPT-M). The WASI-II and NIHTB-CB were repeated annually. Mean participant data from the baseline WASI-II and NIHTB-CB were compared with normative individual measure and composite scores using a one-sample t-test. The NIHTB-CB normative mean is a t-score of 50 with a SD of 10. Baseline results on Medication subtest of the EFPT were compared to previously tested control and stroke groups. Higher scores on the EFPT are indicative of greater executive dysfunction. Differences between Time 1 and Time 2 scores were evaluated using a paired-samples t-test. Univariate analyses were used to describe relationships between cognition and patient factors. Annual magnetic resonance imaging (MRI) was also conducted to assess infarct classification, with completion limited to 12-18 months from consent. Radiographical analyses were reviewed and recorded by the study neuroradiologists. Results: Forty participants were assessed at baseline; 9 completed Time 2 testing. Participant demographic information is presented in Table 1. Compared to the normative population, no significant differences were found on the WASI-II. On the NIHTB-CB, participants scored significantly lower on subtests measuring processing speed (Mean difference -13.8, p Of the 59 participants consented to yearly MRI evaluation, 45 have completed baseline imaging and 1 completed Time 2 imaging. Radiographical impressions reported: 1) overt strokes in 2 participants on transfusions (TF), 1 on hydroxyurea (HU), and 1 on no disease-modifying regimen (ND); 2) SCIs in 6 participants on TF, 6 on HU, and 4 on ND; 3) no infarct in 1 participant on TF, 18 on HU, and 9 on ND. Conclusion: Adults with SCD in this relatively highly educated cohort have marked deficits in executive function, attention, working memory, processing speed, and self-awareness. Cognitive deficits lead to difficulty completing everyday functional and disease-related activities, ranging from medication adherence to productivity in education and employment. Healthcare providers who treat individuals with SCD should be aware of the cognitive impairments in this population. Routine cognitive screening is needed to initiate referrals for cognitive rehabilitation. Disclosures King: Magenta Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novimmune: Research Funding; RiverVest: Consultancy; Tioma Therapeutics (formerly Vasculox, Inc.):: Consultancy; WUGEN: Equity Ownership; Incyte: Consultancy; Amphivena Therapeutics: Research Funding; Cell Works: Consultancy; Bioline: Consultancy; Celgene: Consultancy.

Feeding disorders are common pediatric problems with diverse etiology. They are associated with organic diseases, especially digestive, circulatory and neurological conditions. Psychological factors may also play an important role. We present a case of infant admitted to hospital because of feeding disturbances and poor weight gain. Based on differential diagnostics we excluded organic causes of feeding disturbances in the presented case. Clinical observations and further events let us diagnose an incorrect mother–child relationship as possible reason of feeding disorder in our patient.

Background Dilated cardiomyopathy (DCM) in childhood has a considerable morbidity and mortality and high incidence of heart transplantation. Pulmonary artery banding (PAB) has been proposed in patients with corrected transposition of the great arteries to retrain the sub-pulmonic left ventricle (LV) and to improve a failing sub-aortic right ventricle. We evaluated the short-term and medium-term effects of PAB in young patients with LVDCM. Methods A retrospective single-center observational study was performed to evaluate the possible benefits of a dilatable surgical PAB in infants and young children with LVDCM. Results Reported are 12 patients (10 infants, 2 toddlers) with LVDCM referred for heart transplant who received a surgical PAB. There were no hospital deaths. Clinical functional status improved in all patients. The pressure gradient across the PAB increased within 20 days from 28 ± 7 to 43 ± 15 mm Hg. The LV ejection fraction increased from 14.5% ± 5% pre-PAB to 27% ± 13% at hospital discharge and to 47% ± 10% at 3 to 6 months. The LV end-diastolic diameter (z-score) decreased ( p > 0.001) from 46 ± 6.1 (+7.0 ± 1.3) to 35 ± 15 mm (+3.0 ± 1.3) after 3 to 6 months and to 34 ± 15 mm (+1.3 ± 1.14) after a median age of 2 years (maximum 6.6 years), respectively. Plasma B-type natriuretic peptide levels decreased from 3431 ± 2610 to 288 ± 321 pg/ml at discharge and to 102 ± 96 pg/ml 22 months later. Eight children were subsequently de-banded by transcatheter technique and 6 of them are currently at Ross Heart Failure Classification for Children class I. Two patients, both with non-compaction DCM, deteriorated at 5 and 6 months after PAB debanding and finally died. Conclusion In young children with LVDCM and still-preserved right ventricular function, PAB led to an improvement of LV and mitral valve function by ventricular interaction.

Lesch-Nyhan syndrome is a rare inborn error of metabolism with very poor prognosis. Patients vary in many ways but all seem to have impairments to some degree in uric acid metabolism, motor development, and behavior. A careful evaluation is essential toward making the appropriate diagnosis. A case of infant with motor delay, spasticity, dystonia, and crystalluria is reported. Treatment based on allopurinal (12 mg/kg of body weight/24 h) reduced serum hyperuricemia to values

Purpose Pharmacovigilance methods have advanced greatly during the last decades, making post-market drug assessment an essential drug evaluation component. These methods mainly rely on the use of spontaneous reporting systems and health information databases to collect expertise from huge amounts of real-world reports. The EU-ADR Web Platform was built to further facilitate accessing, monitoring and exploring these data, enabling an in-depth analysis of adverse drug reactions risks. Methods The EU-ADR Web Platform exploits the wealth of data collected within a large-scale European initiative, the EU-ADR project. Millions of electronic health records, provided by national health agencies, are mined for specific drug events, which are correlated with literature, protein and pathway data, resulting in a rich drug–event dataset. Next, advanced distributed computing methods are tailored to coordinate the execution of data-mining and statistical analysis tasks. This permits obtaining a ranked drug–event list, removing spurious entries and highlighting relationships with high risk potential. Results The EU-ADR Web Platform is an open workspace for the integrated analysis of pharmacovigilance datasets. Using this software, researchers can access a variety of tools provided by distinct partners in a single centralized environment. Besides performing standalone drug–event assessments, they can also control the pipeline for an improved batch analysis of custom datasets. Drug–event pairs can be substantiated and statistically analysed within the platform's innovative working environment. Conclusions A pioneering workspace that helps in explaining the biological path of adverse drug reactions was developed within the EU-ADR project consortium. This tool, targeted at the pharmacovigilance community, is available online at https://bioinformatics.ua.pt/euadr/. Copyright © 2012 John Wiley & Sons, Ltd.

Renal impairment because of CNI contributes to long-term morbidity. Therefore, CNI avoiding or sparing treatment strategies are important. In this article, we describe the results of a CNI-free treatment protocol with regard to recovery of renal function. Twenty-eight patients with heart transplantation were switched from CNI regimen to everolimus and mycophenolate, when cGFR was

The present work introduces a novel method for drug research based on the sequential building of linked multivariate statistical models, each one introducing a different level of drug description. The use of multivariate methods allows us to overcome the traditional one-target assumption and to link in vivo endpoints with drug binding profiles, involving multiple receptors. The method starts with a set of drugs, for which in vivo or clinical observations and binding affinities for potentially relevant receptors are known, and allows obtaining predictions of the in vivo endpoints highlighting the most influential receptors. Moreover, provided that the structure of the receptor binding sites is known (experimentally or by homology modeling), the proposed method also highlights receptor regions and ligand-receptor interactions that are more likely to be linked to the in vivo endpoints, which is information of high interest for the design of novel compounds. The method is illustrated by a practical application dealing with the study of the metabolic side effects of antipsychotic drugs. Herein, the method detects related receptors confirmed by experimental results. Moreover, the use of structural models of the receptor binding sites allows identifying regions and ligand-receptor interactions that are involved in the discrimination between antipsychotic drugs that show metabolic side effects and those that do not. The structural results suggest that the topology of a hydrophobic sandwich involving residues in transmembrane helices (TM) 3, 5, and 6, as well as the assembling of polar residues in TM5, are important discriminators between target/antitarget receptors. Ultimately, this will provide useful information for the design of safer compounds inducing fewer side effects.

Streszczenie Autorzy przedstawiają opis przebiegu klinicznego rozyczki wrodzonej u 5-tygodniowego niemowlecia hospitalizowanego na roznych oddzialach z powodu wielonarządowych objawow klinicznych wymagających wielospecjalistycznych interwencji, w tym zabiegowych.

Summary: DisGeNET is a plugin for Cytoscape to query and analyze human gene–disease networks. DisGeNET allows user-friendly access to a new gene–disease database that we have developed by integrating data from several public sources. DisGeNET permits queries restricted to (i) the original data source, (ii) the association type, (iii) the disease class or (iv) specific gene(s)/disease(s). It represents gene–disease associations in terms of bipartite graphs and provides gene centric and disease centric views of the data. It assists the user in the interpretation and exploration of the genetic basis of human diseases by a variety of built-in functions. Moreover, DisGeNET permits multicolouring of nodes (genes/diseases) according to standard disease classification for expedient visualization. Availability: DisGeNET is compatible with Cytoscape 2.6.3 and 2.7.0, please visit http://ibi.imim.es/DisGeNET/DisGeNETweb.html for installation guide, user tutorial and download Contact: lfurlong@imim.es Supplementary information: Supplementary data are available at Bioinformatics online.

Drug-drug interactions (DDI) account for 30% of all adverse drug reactions, which are the fourth leading cause of death in the US. Current methods for post marketing surveillance primarily use spontaneous reporting systems for learning DDI signals and validate their signals using the structured portions of Electronic Health Records (EHRs). We demonstrate a fast, annotation-based approach, which uses standard odds ratios for identifying signals of DDIs from the textual portion of EHRs directly and which, to our knowledge, is the first effort of its kind. We developed a gold standard of 1,120 DDIs spanning 14 adverse events and 1,164 drugs. Our evaluations on this gold standard using millions of clinical notes from the Stanford Hospital confirm that identifying DDI signals from clinical text is feasible (AUROC=81.5%). We conclude that the text in EHRs contain valuable information for learning DDI signals and has enormous utility in drug surveillance and clinical decision support.

In biomedical research, network analysis provides a conceptual framework for interpreting data from high-throughput experiments. For example, protein-protein interaction networks have been successfully used to identify candidate disease genes. Recently, advances in clinical text processing and the increasing availability of clinical data have enabled analogous analyses on data from electronic medical records. We constructed networks of diseases, drugs, medical devices and procedures using concepts recognized in clinical notes from the Stanford clinical data warehouse. We demonstrate the use of the resulting networks for clinical research informatics in two ways—cohort construction and outcomes analysis—by examining the safety of cilostazol in peripheral artery disease patients as a use case. We show that the network-based approaches can be used for constructing patient cohorts as well as for analyzing differences in outcomes by comparing with standard methods, and discuss the advantages offered by network-based approaches.

Background Juvenile idiopathic arthritis is the most common rheumatic disease in children. Chronic uveitis is a common and serious comorbid condition of juvenile idiopathic arthritis, with insidious presentation and potential to cause blindness. Knowledge of clinical associations will improve risk stratification. Based on clinical observation, we hypothesized that allergic conditions are associated with chronic uveitis in juvenile idiopathic arthritis patients. Methods This study is a retrospective cohort study using Stanford’s clinical data warehouse containing data from Lucile Packard Children’s Hospital from 2000–2011 to analyze patient characteristics associated with chronic uveitis in a large juvenile idiopathic arthritis cohort. Clinical notes in patients under 16 years of age were processed via a validated text analytics pipeline. Bivariate-associated variables were used in a multivariate logistic regression adjusted for age, gender, and race. Previously reported associations were evaluated to validate our methods. The main outcome measure was presence of terms indicating allergy or allergy medications use overrepresented in juvenile idiopathic arthritis patients with chronic uveitis. Residual text features were then used in unsupervised hierarchical clustering to compare clinical text similarity between patients with and without uveitis. Results Previously reported associations with uveitis in juvenile idiopathic arthritis patients (earlier age at arthritis diagnosis, oligoarticular-onset disease, antinuclear antibody status, history of psoriasis) were reproduced in our study. Use of allergy medications and terms describing allergic conditions were independently associated with chronic uveitis. The association with allergy drugs when adjusted for known associations remained significant (OR 2.54, 95% CI 1.22–5.4). Conclusions This study shows the potential of using a validated text analytics pipeline on clinical data warehouses to examine practice-based evidence for evaluating hypotheses formed during patient care. Our study reproduces four known associations with uveitis development in juvenile idiopathic arthritis patients, and reports a new association between allergic conditions and chronic uveitis in juvenile idiopathic arthritis patients.

Background: Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are being used in ‘real-world’ settings. Objective: To describe a strategy that identifies potentially drug-induced acute myocardial infarction (AMI) from a large international healthcare data network. Methods: Post-marketing safety surveillance was conducted in seven population-based healthcare databases in three countries (Denmark, Italy, and the Netherlands) using anonymised demographic, clinical, and prescription/dispensing data representing 21,171,291 individuals with 154,474,063 person-years of follow-up in the period 1996–2010. Primary care physicians’ medical records and administrative claims containing reimbursements for filled prescriptions, laboratory tests, and hospitalisations were evaluated using a three-tier triage system of detection, filtering, and substantiation that generated a list of drugs potentially associated with AMI. Outcome of interest was statistically significant increased risk of AMI during drug exposure that has not been previously described in current literature and is biologically plausible. Results: Overall, 163 drugs were identified to be associated with increased risk of AMI during preliminary screening. Of these, 124 drugs were eliminated after adjustment for possible bias and confounding. With subsequent application of criteria for novelty and biological plausibility, association with AMI remained for nine drugs (‘prime suspects’): azithromycin; erythromycin; roxithromycin; metoclopramide; cisapride; domperidone; betamethasone; fluconazole; and megestrol acetate. Limitations: Although global health status, co-morbidities, and time-invariant factors were adjusted for, residual confounding cannot be ruled out. Conclusion: A strategy to identify potentially drug-induced AMI from electronic healthcare data has been proposed that takes into account not only statistical association, but also public health relevance, novelty, and biological plausibility. Although this strategy needs to be further evaluated using other healthcare data sources, the list of ‘prime suspects’ makes a good starting point for further clinical, laboratory, and epidemiologic investigation. This research has been funded by the European Commission’s Seventh Framework Programme (FP7/2007–2013) under grant no. 215847–The EU-ADR Project.

Cytoscape is an open-source software for visualizing, analyzing, and modeling biological networks. This chapter explains how to use Cytoscape to analyze the functional effect of sequence variations in the context of biological networks such as protein-protein interaction networks and signaling pathways. The chapter is divided into five parts: (1) obtaining information about the functional effect of sequence variation in a Cytoscape readable format, (2) loading and displaying different types of biological networks in Cytoscape, (3) integrating the genomic information (SNPs and mutations) with the biological networks, and (4) analyzing the effect of the genomic perturbation onto the network structure using Cytoscape built-in functions. Finally, we briefly outline how the integrated data can help in building mathematical network models for analyzing the effect of the sequence variation onto the dynamics of the biological system. Each part is illustrated by step-by-step instructions on an example use case and visualized by many screenshots and figures.

Following microbial pathogen invasion, the human immune system of activated phagocytes generates and releases the potent oxidant hypochlorous acid (HOCl), which contributes to the killing of menacing microorganisms. Though tightly controlled, HOCl generation by the myeloperoxidase-hydrogen peroxide-chloride system of neutrophils/monocytes may occur in excess and lead to tissue damage. It is thus of marked importance to delineate the molecular pathways underlying HOCl cytotoxicity in both microbial and human cells. Here, we show that HOCl induces the generation of reactive oxygen species (ROS), apoptotic cell death and the formation of specific HOCl-modified epitopes in the budding yeast Saccharomyces cerevisiae. Interestingly, HOCl cytotoxicity can be prevented by treatment with ROS scavengers, suggesting oxidative stress to mediate the lethal effect. The executing pathway involves the pro-apoptotic protease Kex1p, since its absence diminishes HOCl-induced production of ROS, apoptosis and protein modification. By characterizing HOCl-induced cell death in yeast and identifying a corresponding central executor, these results pave the way for the use of Saccharomyces cerevisiae in HOCl research, not least given that it combines both being a microorganism as well as a model for programmed cell death in higher eukaryotes.

With increasing adoption of electronic health records (EHRs), there is an opportunity to use the free-text portion of EHRs for pharmacovigilance. We present novel methods that annotate the unstructured clinical notes and transform them into a deidentified patient-feature matrix encoded using medical terminologies. We demonstrate the use of the resulting high-throughput data for detecting drug-adverse event associations and adverse events associated with drug-drug interactions. We show that these methods flag adverse events early (in most cases before an official alert), allow filtering of spurious signals by adjusting for potential confounding, and compile prevalence information. We argue that analyzing large volumes of free-text clinical notes enables drug safety surveillance using a yet untapped data source. Such data mining can be used for hypothesis generation and for rapid analysis of suspected adverse event risk.

Signal-detection algorithms (SDAs) are recognized as vital tools in pharmacovigilance. However, their performance characteristics are generally unknown. By leveraging a unique gold standard recently made public by the Observational Medical Outcomes Partnership (OMOP) and by conducting a unique systematic evaluation, we provide new insights into the diagnostic potential and characteristics of SDAs that are routinely applied to the US Food and Drug Administration (FDA) Adverse Event Reporting System (AERS). We find that SDAs can attain reasonable predictive accuracy in signaling adverse events. Two performance classes emerge, indicating that the class of approaches that address confounding and masking effects benefits safety surveillance. Our study shows that not all events are equally detectable, suggesting that specific events might be monitored more effectively using other data sources. We provide performance guidelines for several operating scenarios to inform the trade-off between sensitivity and specificity for specific use cases. We also propose an approach and demonstrate its application in identifying optimal signaling thresholds, given specific misclassification tolerances.

Die Neuronavigation spielt in der modernen Neurochirurgie eine wichtige Rolle und bietet die Moglichkeit der intraoperativen Visualisierung von Zielstrukturen, aber auch funktionellen Risikostrukturen. Nach Einfuhrung in die Grundprinzipien der Navigation sowie der sog. multimodalen Neuronavigation soll hier detaillierter auf die praoperative fMRT- und DTI-Diagnostik sowie deren intraoperativen Einsatz eingegangen werden. Die intraoperative Visualisierung von funktionellen Strukturen ist bei manchen neurochirurgischen Eingriffen von essenzieller Bedeutung. Hervorzuheben ist hier die Resektion hirneigener Tumoren. Im neurochirurgischen Behandlungskonzept von Tumoren stellt die maximal sichere Tumorvolumenresektion den operativen Standard fur intrazerebrale Lasionen dar. Was fur benigne Prozesse unbestritten ist, wurde fur nieder- und hohergradige hirneigene Tumore mit ihrem histopathologisch gesicherten infiltrativen Wachstumsmuster in der Literatur lange diskutiert (Keles et al. 2006; Pope et al. 2005), da eine Korrelation zwischen maximaler Tumorvolumenreduktion und verlangerter mittlerer Uberlebenszeit der Patienten lange nicht sicher nachgewiesen werden konnte. Mittlerweile favorisiert die aktuelle Literatur jedoch auch fur diese Art von Lasionen die maximale Tumorvolumenreduktion bei gleichzeitigem Erhalt der neurologischen Funktionalitaten als positiv pradiktiven Faktor fur ein verbessertes Outcome der Patienten (Claus et al. 2005; Keles et al. 1999; Lacroix et al. 2001; Sanai u. Berger 2008; Stummer et al. 2006). Die Abgrenzung der Tumorgrenzen vom physiologischen Hirnparenchym stellt jedoch auch fur den erfahrenen Neurochirurgen eine Herausforderung dar, da sich pathologisches und gesundes Gewebe auch unter Mikroskopvergroserung oftmals nicht signifikant unterscheiden. Um dieses Ziel der maximal sicheren Resektion zu erreichen, macht sich die Neurochirurgie die sog. computergestutzte multimodale Neuronavigation zunutze.

Cytoscape is an open-source software for visualizing, analyzing, and modeling biological networks. This chapter explains how to use Cytoscape to analyze the functional effect of sequence variations in the context of biological networks such as protein-protein interaction networks and signaling pathways. The chapter is divided into five parts: (1) obtaining information about the functional effect of sequence variation in a Cytoscape readable format, (2) loading and displaying different types of biological networks in Cytoscape, (3) integrating the genomic information (SNPs and mutations) with the biological networks, and (4) analyzing the effect of the genomic perturbation onto the network structure using Cytoscape built-in functions. Finally, we briefly outline how the integrated data can help in building mathematical network models for analyzing the effect of the sequence variation onto the dynamics of the biological system. Each part is illustrated by step-by-step instructions on an example use case and visualized by many screenshots and figures.

In Brassica vegetables, heating processes lead to thermally induced degradation of glucosinolates (GSLs), resulting in the formation of nitriles and isothiocyanates (ITCs). To date, the mechanism is not yet satisfyingly elucidated. Thermally induced degradation of the model GSL sinigrin was studied in dry as well as aqueous medium at different pH values and temperatures. The influence of the presence of iron ions and plant matrix (broccoli sprouts powder) on the degradation was studied as well. Next to the degradation of the GSL, the formation of nitrile and ITC and the release of sugar derivatives were investigated. Because d-glucose and ITC are main thermal breakdown products under aqueous conditions, hydrolysis seems to be the initial step in the degradation pathway during cooking. In contrast, under dry conditions, the desulfo-sinigrin was identified as a main intermediary thermal breakdown product for the first time. Further, degradation of the desulfo-GSL results in the release of d-thioglucose and the corresponding nitrile. Iron(II) ions and plant matrix influence the thermal stability of the GSL and favor the formation of nitriles.