Little is known about the health-related quality of life (HRQoL) and work-related stress and its risk factors among white-collar businessmen and management workers that migrate to high-income developing countries. A structural questionnaire survey was administered to 156 white-collar Taiwanese management personnel of representative companies of their industries in Taiwan, who were assigned long-term job positions in China. Questionnaire content included demographics and medical history, self-reported physical and mental conditions, personal lifestyle and behavior, Beck Depression Inventory, and information on HRQoL. White-collar migrant workers reported a high prevalence of alcohol consumption (72.4%) and perceived work-related stress (62.2%), and a lower prevalence of regular exercise (12.2%). Workers with higher levels of perceived work-related stress reported more alcohol consumption, a history of hyperlipidemia, and a higher prevalence of self-reported neck pain, poor sleep, and mild/moderate/severe depression. In our primary multivariate risk model to determine lifestyle and work-related stress variables and HRQoL, perceived work-related stress and a feeling of depression negatively impacted both the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores of the SF-36 health survey. Hyperlipidemia and self-reported neck pain were associated with significantly lower PCS scores, whereas cardiovascular disease, gastric ulcer, and poor sleep were associated with statistically lower MCS scores. White-collar migrant workers are generally younger with high socioeconomic status. Perceived work-related stress and a feeling of depression indirectly affect HRQoL. Hyperlipidemia, self-reported neck pain, cardiovascular disease, gastric ulcer, and poor sleep also had a significant negative impact on HRQoL. Worker migration and labor mobility are increasingly common phenomena in many regions of the World. Migrant workers contribute to the economic growth of high-income countries, often serving as the labor force for the dangerous, dirty, and degrading jobs the “3 Ds”) that national workers are reluctant to perform . Migrant Ds” thatIncreased stress from competition and the opportunity to gain an international market share have led to the trend for white-collar businessmen or management workers to migrate to high-income developing countries for work. The term ‘white-collar migrant worker’ refers to a salaried professional or an educated worker who performs semi-professional office, administrative, and sales coordination tasks. Little is known, however, about the health-related quality of life (HRQoL), work-related stress, and risk factors of migration processes of white-collar migrant workers. In the present study, we examined a group of Taiwanese white-collar migrant workers from two representative companies in Taiwan that work in mainland China, a relatively homogeneous management personnel population with regard to socioeconomic background. We focused on HRQoL because HRQoL reflects a person’s perception of the quality of their physical and mental health over time and is closely related to the perceived burden of a person’s self-report of chronic disease and behavioral risk factors. From a broader perspective, HRQoL is considered a broad measure of health status and the patient’s point of view is recognized to be an important component for self-assessment of health care outcomes and self-assessed health status, and is a more powerful predictor of mortality and morbidity than many objective measures of health . This stA cross-sectional survey of health status and HRQoL among Taiwanese white-collar migrant workers assigned to work in China was conducted from 1 August 2006 to 30 April 2008. All white-collar management migrant workers in China of two Taiwanese enterprises, Company A (computer hardware and electronics manufacturer) and Company F (plastics manufacturer) were invited to participate in this study. Company A is a multinational computer hardware and electronics company headquartered in Taiwan. Its products include motherboards, desktops, laptops, monitors, tablet PCs, servers, and mobile phones. It appears in BusinessWeek’s “InfoTech 100”and “Asia’s Top 10 IT Companies” rankings. Company A has manufacturing facilities in Taiwan , China (Suzhou), Mexico (Ciudad Juárez), and the Czech Republic (Ostrava). Company A’s Hi-Tech Park, located in Suzhou, China, covers 540,000 square meters. In this study, we investigated 41 white-collar management migrant workers in the China (Suzhou) manufacturing facility. Company F’s main business area is intermediate raw materials for plastics. Company F’s overseas expansion has focused primarily on the United States and China, and it is one of the largest manufacturers of polyvinyl chloride resins in the world. In China, Company F’s manufacturing facility is mostly located in Kunshan, Nantong, Ningbo, and Fujian Province. In this study, we investigated 118 white-collar management migrant workers in Kunshan, Nantong, Ningbo, and Fujian Province, China. We defined white-collar management migrant workers as those with a superior educational level and high compensation level; hence, they were externally assigned to deal with overseas management and provide professional supervision, and they served in their jobs for at least three months. They usually worked about 8 hours a day, and their positions included specific job responsibilities, such that their bonuses were largely tied to individual performance. Two research companies were selected for the study setting upon consideration of company size, stability, and routine external assignment system. Among the eligible 201 white-collar management migrant workers that we contacted during the study period, 156 provided written informed consent and answered self-administered questionnaires (response rate 77.6%). This study was approved by the Institutional Review Board of the E-Da Hospital (Taiwan).An invitation letter introducing the survey regarding health status and HRQoL among white-collar migrant workers was first mailed to Taiwanese factory directors of the China manufacturing facility, and then telephone and face-to face contact was made approximately 1 week later to confirm approval. The factory’s occupational and environmental health staff helped distribute and collect the self-reported questionnaires. Questionnaires were used to collect data on white-collar management migrant workers’ demographics and medical history, self-reported physical and mental conditions, personal lifestyle and behavior, Beck Depression Inventory (BDI), and HRQoL. Mean time required to complete the survey was 15 min. Participants’ self-reported demographic data were assessed. Level of education was used as a proxy measure for social class and categorized as follows: (1) high school or below or (2) college or above. Marital status was categorized as single, married and living with their spouse , married and living without their spouse (defined as having a spouse that could provide long-distance support) and not currently married . Monthly income was treated as individual work salary from this job and was categorized into one of three grades: $1,600–2,000 dollars, $2,001–2,400 dollars, and more than $2,401 dollars per month. Cigarette smoking history, alcohol intake, and exercise habit were used as lifestyle indices. The participants were asked questions about their cigarette smoking history ; alcohol intake was limited to wine and hard alcohol and was categorized as no habit of alcohol consumption  and a habit of alcohol consumption . Regular exercise was initiated or/and maintained during the month prior to the investigation. Participants were asked, “Have you participated in regular exercise equivalent to a 1-hour walk at least once a week (yes/no) or have you exercised at least 3 times at least once a week to the extent that you breathe deeply or sweat (yes/no)”. To assess perceived work-related stress, we adopted concepts discussed in previous studies ,6,7,8,9.Personal medical history was investigated based on completion of a checklist. The participants were asked whether they had been diagnosed by a physician as having a chronic disease . Sleep problems were surveyed and were defined as difficulty falling asleep; difficulty remaining asleep (more than twice a week); the belief that one is not getting enough sleep, resulting in a disturbance of daily activities or normal social activities; and the use of medication for insomnia, focusing on symptoms during the preceding 4 weeks. Data of self-reported physical symptoms were collected in the study and included neck pain, low back pain, and headache, focusing on symptoms during the preceding 4 weeks.The BDI was originally designed to measure the depth or intensity of depression in psychiatric patients ,11. It hThe Short-Form 36 (SF-36) is a generic measure because it assesses health concepts that represent basic human values relevant to everyone’s functional status and well-being . A ChineThe primary independent variables of interest were perceived work-related stress, medical history, self-reported physical and mental conditions (depressive symptoms and sleep status), and personal lifestyle behavior . The dependent variables in this study were PCS and MCS scores. For the PCS, very low scores indicate substantial limitations in self-care, physical, social, and role activities; severe body pain; or frequent tiredness . For theP < 0.01). Profiles of the 8 scales of the SF-36 among subjects with perceived work-related stress, alcohol consumption, self-reported neck pain, poor sleep, and depression among white-collar Taiwanese workers in China were thus evaluated using the Mann-Whitney test. A P value of less than 0.05 was considered statistically significant. All analyses were performed using Statistical Analysis System  software. Participants’ profiles among white-collar migrant workers were reported. Analyses were based on a published scoring algorithm for the BDI-II and SF-36 accepted guidelines ,14,21,22To determine different risk factors, including lifestyle and work-related stress, medical history, and self-reported symptoms for HRQoL among white-collar migrant workers, a multivariate analysis was used to identify subject characteristics that were independently associated with the summary scores (PCS and MCS) of the SF-36 using separate multiple linear regression models after adjusting for demographic variables. Six sets of regression models were separately calculated controlling for demographic variables. The first to third models estimated the relationship between lifestyle and perceived work-related stress, medical history and sleep problems, and self-report symptoms and PCS, respectively. Models four to six estimated the relationship between lifestyle and perceived work-related stress, medical history and sleep problems, and self-report symptoms and MCS, respectively. We chose six models because the results would more clearly render which risk factor is more important among similar types of predictors and the risk factors that warranted immediate attention.The descriptive characteristics of participants in this study are shown in vs. 63.8%, P = 0.048); they also reported more hyperlipidemia (P = 0.045), greater neck pain (P = 0.009), more poor sleep (P = 0.0315), and more mild /moderate/severe depression (P = 0.009) than those who did not perceive work-related stress. There were no significant differences between the groups among the other variables. A comparison of the demographic information and some of the variables in the subjects with and without perceived work-related stress is shown in P = 0.010) and MCS  scores. Subjects with hyperlipidemia had significantly lower PCS scores , whereas cardiovascular disease, gastric ulcer, and poor sleep were associated with statistically lower MCS scores (P < 0.05). Migrant workers that reported neck pain had significantly lower PCS scores . Having a depressive condition was associated with more negative PCS and MCS scores.The white-collar migrant workers’ 8 scales of the SF-36 according to different health conditions are shown in P = 0.0302) and depression . Similar findings from Japan [The majority of previous studies evaluated blue-collar migrant workers’ health because they often serve as the labor force that fills the “3 D” jobs . At the same time, globalization of the economy and competition of the international market has led to an increase in migration, particularly for white-collar workers. The overall impact of immigration on white-collar workers’ health is poorly understood. In this study, we focused on white-collar workers and found: (1) a high prevalence of alcohol consumption (72.4%) and perceived work-related stress (62.2%) and a lower prevalence of regular exercise (12.2%). People’s susceptibility to disease varies widely and may be a reflection of differences in their biologic predisposition, personality, behavior, and environmental exposure. Based on these data, unhealthy determinant factors were indeed detected in our sample of workers and are dangerous to their health, e.g., continuing work-related stress, greater alcohol intake , and lower levels of physical activities that reduce both heart and lung functions all had negative impact on their health and decreased HRQoL. (2) We found that subjects with perceived work-related stress that consumed more alcohol and those with hyperlipidemia had higher incidence of self-reported neck pain, poor sleep, and mild/moderate/severe depression. Multivariate analysis revealed a significant association between work-related stress and neck pain , while neck pain negatively impacted PCS scores of the SF-36 . Previous reports also demonstrated strong relationships between psychologic distress, job demands , low job control, and pain at multiple sites [Our data revealed a significant association between work-related stress and neck pain (le sites . Althougle sites ,32. Indile sites : arthritIn the present study, white-collar employee health was used as the starting point to conduct a preliminary survey. We used a relatively homogenous sample of subjects who were similar in ethnicity and sociodemographic characteristics. On the other hand, there are some limitations to our study. First, this study was cross-sectional in design; therefore, only association and not causation could be evaluated. Second, in the beginning, this study focused on exploring white-collar migrant workers’ HRQoL and its related risk factors. We underestimated the impact of job stress on HRQoL among white-collar migrant workers, however, and therefore neglected to use a standardized instrument for measuring job stress. The dichotomous variable that we used is not likely to provide nearly enough information. For the assessment of socioeconomic status, co-morbidities and work-related stress, we used a dichotomized classification, which was overly simplistic and might have biased the results. Future studies should adopt a richer “work-related stress” instrument to measure these factors to obtain more detailed data, which would be much more valuable. Third, a selection bias due to healthy-worker effect was inevitable. Excluding those who refused to participate and could not be reached possibly due to a health issue or medical leave, removes a disproportionate number of workers with declining HRQoL, and may have biased the results of the study. This would lead to an underestimation of the quality of life scores and reduce the strength of the associations. In other words, excluded subjects likely included more unhealthy subjects than included subjects; hence, the impact on HRQoL is likely to be greater than our results indicate. The research indicates that white-collar migrant workers are young with a high socioeconomic status compared with blue-collar migrant workers. In the present study, however, we found that except for higher physical health scores, the subjects scored lower than expected on scales of general heath perceptions, vitality/energy, and mental health. Subjects with perceived work-related consumed more alcohol and more frequently reported a history of hyperlipidemia, with more self-reports of neck pain, poor sleep, and mild/moderate/severe depression. A significant association between perceived work-related stress and depressive status indirectly affects HRQoL.


Schizophrenia is characterized by aberrant intrinsic functional connectivity (iFC) within and between intrinsic connectivity networks (ICNs), including the Default Mode- (DMN), Salience- (SN), and Central Executive Network (CEN). The anterior insula (AI) of the SN has been demonstrated to modulate DMN/CEN interactions. Recently, we found that the dependence of DMN/CEN interactions on SN’s right AI activity is altered in patients with schizophrenia in acute psychosis and related to psychotic symptoms, indicating a link between aberrant AI, DMN, CEN, and psychosis. However, since structural alterations of the insula are also present during psychotic remission and associated with negative symptoms, impaired AI interaction might be relevant even for psychotic remission and corresponding symptoms. Twelve patients with schizophrenia during psychotic remission (SR) and 12 healthy controls were assessed using resting-state fMRI and psychometric examination. High-model-order independent component analysis of fMRI data revealed ICNs including DMN, SN, and CEN. Scores of iFC within (intra-iFC) and between (inter-iFC) distinct subsystems of the DMN, SN, and CEN were calculated, compared between groups and correlated with the severity of symptoms. Intra-iFC was altered in patients’ SN, DMN, and CEN, including decreased intra-iFC in the left AI within the SN. Patients’ inter-iFC between SN and CEN was increased and correlated with the severity of negative symptoms. Furthermore, decreased intra-iFC of the left AI correlated with both severity of negative symptoms and increased inter-iFC between SN and CEN. Our result provides first evidence for a relationship between AI dysfunction and altered between-network interactions in schizophrenia during psychotic remission, which is related to the severity of negative symptoms. Together with our previous results, data suggest specific SN/DMN/CEN reorganization in schizophrenia with distinct insular pathways for distinct symptom dimensions. Schizophrenia is a severe mental disorder associated with aberrant functional and structural connectivity within and between intrinsic connectivity networks (ICNs), including the Default Mode- (DMN), Salience- (SN), and Central Executive Network (CEN) Menon, . ICNs arMore specifically, the DMN includes primarily the ventromedial prefrontal cortex, the posterior cingulate cortex, bilateral inferior parietal cortex, and the middle temporal lobe and is involved in self-related/internally oriented processes  within the SN linked to aberrant DMN/CEN interactions in schizophrenia? Recently, it has been demonstrated that the anterior insula within the SN is crucial for modulating interactions between DMN-mediated self-related and CEN-mediated external-task directed processes in response to cognitive demands , patients approved an investigation during state of remission. Patients were free of any current or past neurological or internal systemic disorder, current or past depressive or manic episode, substance abuse (except nicotine), and cerebral pathology in MRI. The mean duration of illness was 4.11 years (SD = 3.29 years), the mean number of hospital stays was 4.00 (SD = 1.07). Four out of 12 patients were free of antipsychotic medication. All other patients received mono- or dual therapy with atypical antipsychotic medication, including Amisulpride (n = 1 case), Olanzapine (n = 1), Clozapine (n = 3), Quetiapine (n = 3), Risperidone (n = 2), and Aripiprazole (n = 1) . fMRI data were obtained by using a gradient echo EPI sequence .MRI was performed on a three T MR scanner  using an eight-channel phased-array head coil. For co-registration and volumetric analysis, T1-weighted anatomical data were obtained by using a magnetization-prepared rapid acquisition gradient echo sequence  and HC yielded no significant results regarding translational  and rotational movements of any direction . Signal-to-noise ratio of fMRI data was not different between patients with schizophrenia during state of remission  and HCs .For each participant, first three functional scans of fMRI were discarded due to magnetization effects. SPM8  was used for motion correction, spatial normalization into the stereotactic space of the Montreal Neurological Institute (MNI) and spatial smoothing with an 8 mm × 8 mm × 8 mm Gaussian kernel. To control for differences in motion between groups, excessive head motion  was applied as exclusion criteria -corrected for multiple comparisons]. To analyze group differences, participants’ spatial maps were entered into two-sample t-tests with age, sex and total GM volumes [see Voxel-based Morphometry Analysis. for detailed presentation of calculation of total GM] as covariates-of-no-interest (p < 0.05 FWE-corrected).To statistically evaluate intra-iFC of selected ICs, we calculated voxel-wise one-sample z-scores using Fisher’s z-transformation and entered into two-sample t-tests with age, sex, and total GM volumes  as covariate-of-no-interest .To statistically evaluate inter-iFC between selected ICs, subject specific ICN TCs were detrended, despiked, filtered using a fifth-order Butterworth low-pass filter with a high frequency cutoff of 0.15 Hz, and pairwise correlated by Pearson’s correlation, following the approach of Jafri et al. . To asset-tests on patients’ reconstructed intra-iFC maps for the SN and masked the result with a mask derived from the two-sample-t-test contrasting patients from HCs. Subsequently, we extracted principle eigenvariates of the clusters representing intra-iFC of the left and right AI within the SN. Then we used eigenvariate-scores for partial correlation analyses of Fisher-z-transformed inter-iFC scores and PANSS scores of total positive and negative PANSS scores, respectively, including age, sex, total GM, and CPZ as covariates of no interest . To study the relationship between inter-iFCs and severity of symptoms in patients, we used Fisher-z-transformed inter-iFC scores for partial correlation analyses of total positive and negative PANSS scores, respectively, including age, sex, total GM, and CPZ as covariates of no interest. Results of partial correlation analyses were thresholded at p < 0.05, Bonferroni-corrected for multiple comparisons.Insular dysfunction has been suggested to be associated with various symptom dimensions, including both positive and negative symptoms in schizophrenia Menon, . Accordit-tests were performed. We applied a height threshold (voxel level) of 0.05, family-wise error (FWE) corrected. Global volumes of GM and WM were derived from the first segmentation process. Groups were compared by two-sample t-tests. Finally, we included total GM scores as covariate-of-no-interest in the functional analyses of ICNs.The VBM analysis followed the description provided in Manoliu et al. . The FC In general, both intra-iFC and inter-iFC were almost perfectly in line with findings of Allen et al. , indicatp < 0.05, FWE-corrected).Automated component selection, which was based on spatial templates representing subsystems of the DMN, SN, and CEN . Regarding the SN, patients showed decreased intra-iFC within the bilateral AI. Furthermore, intra-iFC was increased in bilateral ACC within the SN . Patients showed decreased inter-iFC between ipDMN and rvCEN, suggesting a decreased FC between the DMN and CEN. Furthermore, patients showed increased inter-iFC between SN and rvCEN, indicating increased FC between the SN and CEN.Compared to HCs, patients during psychotic remission showed both increased and decreased inter-iFC . In patients, SN’s left AI intra-iFC correlated negatively with inter-iFC between SN and rvCEN (r = −0.96). There was no further significant correlation of SN’s right or left AI intra-iFC with inter-iFC scores.To study the influence of insular SN activity on altered inter-network connectivity in patients, we correlated eigenvariates of SN’s left and right AI group difference clusters with Fisher-z-transformed correlation coefficients of each pair of network TCs . In patients, SN’s left AI’s intra-iFC correlated negatively with the severity of total negative symptoms (r = −0.97) but not with the severity of total positive symptoms. Furthermore, SNs right AI’s intra-iFC correlated positively with the severity of total positive symptoms (r = 0.886). However, this result was not significant when corrected for multiple comparisons. There was no further significant correlation of SN’s right or left AI intra-iFC with behavioral scores.To study the influence of insular SN activity on the severity of positive and negative symptoms in patients, we correlated eigenvariates of SN’s left and right AI group difference clusters with PANSS scores for total positive symptoms and total negative symptoms, respectively . Inter-iFC between SN and rvCEN correlated positively with the severity of total negative symptoms (r = 0.969) but not with the severity of positive symptoms. There was no further significant correlation of inter-iFC across network-pairs with behavioral scores.To study the relationship of between-network interactions with severity of positive and negative symptoms, we correlated inter-iFC scores with PANSS scores for both total positive symptoms and total negative symptoms, respectively . Regarding potential effects of medication, we correlated CPZ with both intra-iFC of each ICN and inter-iFC for each pair of ICNs. CPZ showed no significant effect on both intra-  and inter-iFC , respectively. In addition, we included total GM and CPZ-scores as covariate-of-no-interest in the functional analyses of ICNs to account for these measures as potential confounders.Regarding potential alterations in brain structure, voxel-wise tests yielded no regional GM or WM differences between groups. Although slightly decreased, total GM was not significantly changed in patients . Although this result is well in line with previous findings (Palaniyappan et al., In accordance to our hypothesis Menon, , we founThese results are in line within the suggested disruption of the AI’s control function for between-network interactions in schizophrenia, which may persist even during psychotic remission and may be related to distinct symptom dimensions (Palaniyappan and Liddle, Our findings suggest an asymmetric involvement of the AI in patients with schizophrenia as a function of state of disease. While the intra-iFC within the left AI was associated with both altered interactions between SN and CEN and severity of negative symptoms in patients during state of remission Figure  and 7, tIn the following we want to make three further comments that may help to better evaluate and contextualize our findings centered on the SN.In contrast to the current study, Woodward et al.  found noAlthough increasing evidence for functional (White et al., Current results are well in line with the aberrant proximal salience model of Palaniyappan and Liddle . ProximaCompared to HCs, patients showed decreased intra-iFC in both ACC and PCC within the DMN, while inter-iFC between DMN’s subsystems was not altered. Although alterations in FC within the DMN in patients with schizophrenia are frequently reported during both task (Garrity et al., In the present study, we adopted a recently proposed pipeline for ICA of resting-state fMRI data (Allen et al., Compared to HCs, patients showed increased intra-iFC in the left inferior temporal gyrus, while inter-iFC between CEN’s subsystems was not altered. Heterogeneous alterations within the CEN have been reported in schizophrenia, including both increased and decreased intra-iFC within the CEN during rest (Woodward et al., Compared to HCs, patients showed decreased inter-iFC between ipDMN and rvCEN, suggesting an aberrant inter-network connectivity between DMN and CEN. It has been suggested that schizophrenia is characterized by a disrupted relationship between the task-negative DMN and task-positive CEN (Williamson, We acknowledge several limitations, which have to be considered in the present study. Firstly, antipsychotic drugs have been shown to have an impact on FC in patients with schizophrenia (Sambataro et al., Secondly, limitations of the ICA have to be taken into consideration, including the arbitrary model-order selection and subjective bias in selection of the components of interest (Cole et al., Results provide evidence that left anterior insular dysfunction within the SN is selectively associated with both aberrant between-network interactions and severity of negative symptoms in patients with schizophrenia during psychotic remission. Together with correspondent findings concerning the right anterior insula in patients during psychosis, these findings suggest that the relationship between insular dysfunction and altered between-network interactions is a characteristic feature of schizophrenia, with possibly distinct insular pathways for distinct symptom dimensions.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Here, we solve this problem with a novel iterative method, based on the expectation maximization algorithm, that reconstructs full-length small subunit gene sequences and provides estimates of relative taxon abundances. We apply the method to natural and simulated microbial communities, and correctly recover community structure from known and previously unreported rRNA gene sequences. An implementation of the method is freely available at  Characterization of microbial community composition is most often done with a phylogenetic marker gene, most commonly the small subunit ribosomal RNA (SSU rRNA) gene . TraditiSearching for SSU genes directly in metagenomic data avoids PCR and primer biases ,17. For de novo assembly near regions with high inter-species sequence identity, such as that found within the SSU gene. Because of these challenges, there are no methods currently available to assemble full-length SSU sequences from short read sequencing data.Most reported metagenomic sequencing has used Sanger or Roche 454 sequencing technologies. The rRNA gene sequences for closely related organisms in these datasets co-assemble. The result is a composite sequence that is not representative of any community member and obscures the real level of diversity. These problems are exacerbated when shorter sequencing reads are used. Typical reads from the Illumina platform currently range from 35 to 125 bp. Additionally, the k-mer-based methods used to assemble short read data can further confound de novo assembly of short read sequencing data is to map reads to a reference sequence, if one is available. Several fast, memory-efficient mapping programs are available, all of which allow for varying levels of error while searching for alignments . These reads were used as input to the assembler Velvet . For the91843. Thin vitro community of Morgan et al. , and the Silva database, and included the best hit for each reconstructed sequence in the resulting multiple sequence alignment. These alignments were imported into MEGA [The nine (for the simple simulated community) and ten  most abundant SSU sequences recovered by the algorithm were used for phylogenetic tree construction. For the simple simulated community, these sequences were aligned with default parameters with muscle  with thento MEGA , and neide novo assembly fragments, a single alignment was built for the three communities with expected, EMIRGE-produced, and assembly-fragment-best hit sequences. A tree was built using FastTree [For the complex community, we aligned EMIRGE-generated SSU sequences with abundance estimates > 0.5% with the sequences from the known community with muscle, and built maximum likelihood trees with RAxML  using thFastTree , and weiFastTree .Bp: base pair; DAPI: 4',6-diamidino-2-phenylindole; EM: expectation maximization; EMIRGE: expectation maximization iterative reconstruction of genes from the environment; E-step: expectation step; M-step: maximization step; OUT: operational taxonomic unit; PCR: polymerase chain reaction; SSU: ribosomal small subunit.The authors declare that they have no competing interests.CSM, BJB, SWS, and JFB designed the study. CSM performed the experiments, and designed and implemented the algorithm. BJB designed the FISH probe. CSM and JFB wrote the manuscript. All authors analyzed the data, and read and approved the final manuscript.FASTA formatted file containing EMIRGE-reconstructed sequences from the simple simulated microbial community.Click here for fileFASTA-formatted file containing EMIRGE-reconstructed sequences from the complex simulated microbial community.Click here for fileFASTA-formatted file containing EMIRGE-reconstructed sequences from the natural microbial community.Click here for file


The number of pulmonary tuberculosis (PTB) patients reported with resistance to first-line anti-tuberculosis drugs after a standardized retreatment regimen in Cameroon is increasing. Hence, the National Tuberculosis Control Program (NTP) implemented, in one of the ten Regions of the country, a pilot programme aimed at performing routine drug susceptibility testing (DST) for previously treated PTB cases. The objectives of the programme were to evaluate the feasibility of monitoring drug resistance among retreatment cases under programme conditions and to measure the presence and magnitude of anti-TB drug resistance in order to inform NTP policies.This retrospective cohort study was conducted in the Littoral Region of Cameroon in 2009. It included all sputum smear positive (SM+) PTB cases registered for retreatment. TB cases were identified and classified according to World Health Organization (WHO) recommendations for national TB programs. Bacterial susceptibility testing to first-line anti-TB drugs was performed using standard culture methods. In 2009, 5,668 TB cases were reported in the Littoral Region, of which 438 (7.7%) were SM + PTB retreatment cases. DST results were available for 216 (49.4%) patients. Twenty six patients (12%) harbored multi-drug resistant (MDR) strains. Positive treatment outcome rates were particularly low in retreatment patients with MDR-TB . Thirteen MDR-TB patients were treated using a standardized MDR treatment regimen. Delivery of laboratory results took on average 17 (12-26) weeks.WHO-recommended routine DST in retreatment patients seems feasible in Cameroon. However, coverage needs to be improved through better management. Moreover, diagnostic delay should be shortened by introducing more rapid diagnostic tools. The high risk of MDR in standard regimen failure cases virtually rules out the standard retreatment regimen for such patients without prior DST. In 2009, about 30,000 or 11% of estimated overall 500, 000 MDR-TB cases were enrolled for second-line treatment. Achieving universal access to diagnosis and treatment of multidrug-resistant and extensively drug-resistant tuberculosis (M/XDR-TB) remains a challenge .In Cameroon, in 2009, the estimated TB incidence rate was 182 cases per 100,000 inhabitants . The totThe Littoral Region has about 3.5 million inhabitants, with some 3 million people living in the economic capital, Douala. TB cases are reported and virtually treated exclusively within a network of 29 functional government or private confessional Basic Management Units (BMU). The number of TB patients treated in the private sector is negligible as anti-TB drugs are not available, neither in private pharmacies nor through drug vendors in the informal sector. Twenty of the BMUs are located in Douala and receive about 75% of the Littoral Region's annual incident cases. More than ninety-five per cent of reported cases originate from the Littoral Region. One of the two MDR-TB treatment centres is situated in Douala. Provider initiated voluntary counselling and testing for HIV with consequent Co-trimoxazole prophylaxis is offered free-of-charge to all newly diagnosed TB-cases. HIV + patients are systematically referred to the nearest HIV/AIDS treatment service for further evaluation of their infection.This study included all consecutively registered SM + PTB retreatment cases with a new episode of TB admitted any one the 29 BMUs of the Littoral Region in Cameroon between 1 January and 31 December 2009 for a standardized retreatment regimen according to NTP guidelines, categorized as "Relapse", "Treatment failure" or "Return after default" (WHO case definitions), and for whom DST results were available [The study excluded all "Other retreatment" cases, i.e. cases with unknown previous treatment outcome, patients returning to treatment with smear-negative PTB or bacteriologically not confirmed extrapulmonary TB as well as cases with non-tuberculosis mycobacteria.TB laboratory technicians in all BMUs had been instructed to keep one fresh morning sputum specimen of all consecutively notified SM + PTB retreatment refrigerated and to ensure their transportation within 72 hours to the Regional TB Reference Laboratory in Douala. Here, a new smear was made after decontamination of the specimens and concentration by centrifugation. According to routine procedures, two slopes of Löwenstein-Jensen (LJ) medium per specimen were inoculated and incubated at 37°C, discarding negative slopes after ten weeks. Positive cultures were then transported to the national TB Reference Laboratory, Centre Pasteur du Cameroun (CPC), for DST using the indirect proportion method on LJ medium . The folThe study protocol was reviewed and approved by the competent administrative authorities and the National Ethics Committee of Cameroon.χ2 test statistic and Fisher exact test where appropriate.TB and demographic data, as well as HIV status, were extracted from the NTP standard TB registers. TB culture and DST results (including delivery dates) were tracked, respectively, through the Regional and National TB Reference laboratories. Culture and DST results were matched with patients registered in the BMUs using the date of registration and the patient's registration number. Main outcome measures were the proportion of reported retreatment cases with DST results available, the proportion of MDR-TB per subcategory of retreatment cases, and the proportion of retreatment cases identified with MDR-TB and treatment success defined as "Cured" or "Treatment completed". Double data entry with data cleaning and analysis was done in Epi Info 6.04 d. Per category data was expressed in percentages, continuous variables as mean and standard variation. All proportions were compared using the p < 0.001). HIV infection rate was 25.9% and slightly higher among female patients. Table In 2009, 5,668 TB-cases were reported in the Littoral Region, of which 528 retreatment cases (9.3%). Of this number, 438 (83.0%) were SM + PTB retreatment cases registered in any of the three sub-categories . Where cultures were negative, failed to grow, were contaminated or where data were missing, patients were excluded as TB could not be confirmed. DST results were available for 216 (49.4%) SM + PTB retreatment cases. The selection of the study population is shown in Figure Table Positive treatment outcome rates did not differ significantly between pansusceptible, monoresistant, and polyresistant patients. However, only twelve out of 26 MDR-TB patients  had a successful treatment outcome due to a high failure rate  (Table Delivery of laboratory results to clinicians took on average 17 (12-26) weeks. Of the 26 diagnosed MDR-TB cases, 13 patients were treated following the standardized MDR treatment regimen; three patients died before the start of MDR-treatment; four patients did not accept another treatment; four patients remained smear-negative up to one-year follow-up; two patients were lost to follow-up, one during retreatment, the other after having being declared cured.In our retrospective cohort study, 51% of SM + PTB retreatment patients showed resistance to one or more anti-TB drugs; those having failed the standard regimen showed at base-line a high rate of MDR-TB; this rate was also important in relapse cases. It cannot be excluded that the relative high failure rate for the retreatment regimen is partly due to primary MDR-TB with subsequent transmission. Recently published data from other Regions of Cameroon suggest an increase in the rate of primary MDR-TB . As predThe study has several limitations, the most important of which is possible selection bias with about half of the cohort excluded due to missing DST results. The incomplete coverage of the target population may have distorted the findings. Yet, all BMUs participated in sampling and the proportion of retreatment subcategories, age and sex distribution, as well as the HIV co-infection rate in the sampled part of the study population and the full target population were comparable. - Secondly, our study was records-based and patients' classification was not controlled. In particular, misclassification of relapse cases as new cases is common under programme conditions; it is possible that the proportion of relapse cases was underestimated. On the other hand, the proportion of retreatment cases with their different subcategories, as well as drug resistance profiles, confirm trends observed in the West Region , the Littoral Region (2008), and the North-West Region (2009) ,11. - FiAs previously described for another Region in the country, we did not observe any association between MDR-TB and HIV . This coDue to very long turn-around times for DST results (> 4 months) with two different laboratories involved and frequent subculturing needed before obtaining DST results, the time for initiating MDR-TB treatment in practice coincided with the 5-month control period. For patients with laboratory-proven MDR-TB but having responded favorably to the standardized retreatment regimen, no MDR treatment was initiated, thus trading off the benefits of a MDR-TB treatment against the fact that the standard retreatment scheme may give positive treatment outcomes and against the possible side effects of the MDR-TB treatment, in particular a prolonged treatment with potentially ototoxic aminoglycosides. Indeed, in our cohort, four  MDR-TB patients who were cured presented no recurrent disease (microscopy and culture negativity) for up to one year after the end of their retreatment. This clinical  decision is debatable .® MTB/RIF) at selected strategic sites to enable early detection of MDR resistance and prioritize high risk patient groups such as TB patients having failed the standard regimen [For almost two decades, country and multi-country studies have gathered overwhelming evidence on unfavorable outcomes in patients failing the standard regimen, mostly those infected by MDR-TB and treated according to the standard WHO-recommended retreatment regimen -20. Two  regimen .Preliminary results of systematic DST for SM + PTB retreatment patients showed that early detection of MDR-TB under program conditions in Cameroon might be feasible if more rapid diagnosis tools required for initiating adequate treatment timely are put in place. Data also suggests that a standardized retreatment regimen is inadequate in Cameroon for failure cases and that there is a significant proportion of relapse cases. Systematic DST for retreatment patients should be implemented country-wide, while improving access to rapid diagnosis.BMU: Basic Management Unit; CI: Confidence interval; CPC: Centre Pasteur de Cameroun; DST: Drug susceptibility testing; E: Ethambutol; Gfx: Gatifloxacin; H: Isoniazid; HIV: Human immunodeficiency virus; Km: Kanamycin; MDR: Multi-drug resistant; NTP: National tuberculosis control program; OR: Odds ratio; PTB: Pulmonary tuberculosis; Pto: Prothionamide; R: Rifampicin; S: Streptomycin; SD: Standard deviation; SM+: Sputum smear positive; TB: Tuberculosis; XDR: Extensively drug resistant; WHO: World health organization; Z: Pyrazinamide.The authors declare that they have no competing interests.JN and NV drafted the manuscript; EF and JLA monitored the data collection, participated in the data analysis, and contributed to the drafting of the manuscript. All authors read and approved the final manuscript.


Radiotherapy plays an important role in the treatment for thoracic cancers. Accurate diagnosis is essential to correctly perform curative radiotherapy. Tumor delineation is also important to prevent geographic misses in radiotherapy planning. Currently, planning is based on computed tomography (CT) imaging when radiation oncologists manually contour the tumor, and this practice often induces interobserver variability. F-18 fluorodeoxyglucose positron emission tomography (FDG-PET) has been reported to enable accurate staging and detect tumor extension in several thoracic cancers, such as lung cancer and esophageal cancer. FDG-PET imaging has many potential advantages in radiotherapy planning for these cancers, because it can add biological information to conventional anatomical images and decrease the inter-observer variability. FDG-PET improves radiotherapy volume and enables dose escalation without causing severe side effects, especially in lung cancer patients. The main advantage of FDG-PET for esophageal cancer patients is the detection of unrecognized lymph node or distal metastases. However, automatic delineation by FDG-PET is still controversial in these tumors, despite the initial expectations. We will review the role of FDG-PET in radiotherapy for thoracic cancers, including lung cancer and esophageal cancer.  Radiotherapy plays an important role in the treatment of thoracic cancers, such as non-small-cell lung cancer (NSCLC), small-cell lung cancer (SCLC), and esophageal cancer , 2. Rece Currently, treatment planning is based on computed tomography (CT) imaging to contour the tumor. Tumor delineation is manually performed by each radiation oncologist in clinical practice, which leads to interobserver variability in tumor delineation. Accurate delineation of tumor volume requires the identification of anatomic borders of tumors based on accurate diagnosis. F-18 fluorodeoxyglucose positron emission tomography (FDG-PET) and PET/CT have been reported to enable accurate staging and to detect the tumor extension compared with CT alone . FDG-PET Thoracic radiotherapy is a key modality of the management for NSCLC patients. Accurate staging is crucial for lung cancer patients because treatment strategy and prognosis drastically differ according to clinical stage. CT imaging contributes to the initial determination for the staging of NSCLC and provides morphologic information of the disease extension. Currently, FDG-PET is performed to diagnose the stage and evaluate the effects of the treatment in clinical use for NSCLC patients. One of the important roles of FDG-PET is to detect unsuspected lymph nodes or extrathoracic metastases , 6. A pr FDG-PET is increasingly performed to define tumor volume for radiotherapy in patients with NSCLC. Accurate contouring of organs is important for radiotherapy and PET imaging is currently expected to be useful in the delineation of gross tumor volume (GTV) . In this Several methods have been examined for GTV delineation after the introduction of FDG-PET  12–25].–25.12–25Several articles have reported the use of standardized uptake volume (SUV) in GTV identification. Paulino and Johnstone have suggested using SUV of 2.5 to autocontour GTV . Hong et Recently, some studies reported a new gradient-based method relied on the water shed transform and hierarchical cluster analysis. This method provided denoised and deblurred images with an edge-preserving filter and a constrained iterative deconvolution algorithm, leading a better estimation of the gradient intensity. Wanet et al. compared a gradient-based segmentation method, a source-to-background ratio method, and a 40% to 50% of SUV max method with surgical specimens of 10 patients with NSCLC . All pat Despite these several techniques for the delineation of tumor volume having been reported in recent years, a gold standard method has not been established to contour GTV automatically. However, FDG-PET has the additional information that aids radiation oncologists to delineate GTV, indicating that FDG-PET should be utilized when tumor volume is delineated in NSCLC patients.P < 0.01). Recently, van Barrdwijk et al. also reported that PET/CT-based autocontouring decreased interobserver variability in delineation of the primary tumor and nodal legions [Interobserver variability in regard to GTV definition is a serious problem in the treatment planning for NSCLC , 27. Cal legions . These s Currently, more patients have been treated by stereotactic body radiotherapy (SBRT) for early-stage NSCLC , 2. ReceP < 0.001). Multivariate analysis showed that only the SUVmax of a primary tumor was a significant predictor for local recurrence (P = 0.002). The authors concluded that a high SUVmax might be considered for dose escalation to improve local control in NSCLC. Hoopes et al. also reported that 58 patients with medically inoperable stage I NSCLC treated by SBRT [n = 26), recurrent lung cancer (n = 12), and solitary lung metastases (n = 13) [ Takeda et al. evaluated the correlation between pretreatment SUVmax on FDG-PET and local recurrence in 95 patients with NSCLC . Total d by SBRT . Total d(n = 13) . Most pa These findings suggest that FDG-PET is useful for accurate staging and treatment planning in stage I NSCLC treated by SBRT. However, it has been controversial whether pretreatment SUVmax is prognostic factor for treatment outcomes, such as local control and overall survival. Prospective studies are warranted to establish the role of FDG-PET in SBRT for NSCLC patients.For patients with NSCLC, local failure after radiation therapy is a significant issue. Sura et al. reported FDG-PET as a method to assume the pattern of local failure after radiation therapy . They an Similarly, Abramyuk et al. also reported the detection of recurrence using PET/CT . They ev Elective nodal irradiation to the mediastinal lymph regions in the treatment of stage III NSCLC patients is still a controversy , 38. RosFDG-PET can contribute to accurate evaluation of nodal lesions, compared with CT alone , 42. De SCLC accounts for 20–25% of all newly diagnosed lung cancers. SCLC often represents an aggressive clinical course and high incidence of distant metastasis because of rapid tumor growth. Despite aggressive treatment, the prognosis remains poor .P = 0.019), while CT imaging did not (P = 0.055). These studies recommended that FDG-PET should be performed for initial staging in limited-disease SCLC patients. Although accurate staging is essential for determining the treatment strategy in SCLC, it is difficult to evaluate the extension of disease accurately, and especially mediastinum lymph node metastases. Fischer et al. prospectively examined the role of PET/CT compared with standard staging (CT and bone scintigraphy) in 29 SCLC patients . In thei Compared with NSCLC, few studies have been performed regarding the delineation based on FDG-PET for SCLC. FDG-PET in SCLC patients may improve the delineation of tumor volume as well as NSCLC.For limited-disease SCLC, elective nodal irradiation for mediastinal lymph node regions has been considered necessary to reduce lymph node failure. However, some clinicians have attempted to avoid elective nodal irradiation because extended radiotherapy volume leads to severe side effects. Baas et al. conducted a phase II study of involved-field radiotherapy for limited-disease SLCL staged by CT imaging . They re Currently, FDG-PET is expected to determine whether elective nodal irradiation is necessary or not. Two recent studies have shown the usefulness of FDG-PET in omitting elective nodal irradiation in SCLC , 53. van Another possible role of FDG-PET in SCLC is in the evaluation of the therapeutic response. A preliminary study showed that FDG-PET could predict the outcome of treatment by radiotherapy or chemotherapy . In conclusion, the role of FDG-PET in SCLC has been established for staging use. Although the use of FDG-PET in radiation treatment planning for SCLC is still controversial, involved-field irradiation based on FDG-PET is an attractive strategy. FDG-PET-based treatment planning will change the strategy for limited-disease SCLC.In the treatment of esophageal cancer, radiotherapy is commonly used in combination with chemotherapy. Currently, radiotherapy requires accurate target volume definition based on treatment planning by CT scan. Although planning-CT-based target volume definition is considered the gold standard in esophageal cancer, applying FDG-PET to treatment planning may have several advantages, such as accurate staging and delineation of tumor.P = 0.004). Van Vliet et al. performed a meta-analysis to evaluate the diagnostic performance of CT and FDG-PET in staging of esophageal cancer [ FDG-PET has been considered useful in the staging process of esophageal cancer . Flamen l cancer . The senAccurate delineation of esophageal tumor is important for successful radiotherapy. The additional information provided by FDG-PET is expected to improve tumor delineation and accurate staging of lymph nodes and distant metastases. Several studies have investigated the optimal method for delineating the target volume by FDG-PET. Most studies used visualized interpretation for tumor delineation –61. Mour Konski et al. used SUV 2.5 to delineate the tumor extension and evaluated the CT-based tumor length in 25 esophageal cancer patients . The aut Recent studies indicated that SUV 2.5 may be an optimal threshold, but autocontouring using this threshold is not satisfactory. Further investigations are required to utilize FDG-PET in the tumor delineation for esophageal cancer in clinical use.Another method to utilize FDG-PET in treatment planning is to reduce interobserver variability. Schreurs et al. evaluated the tumor volumes delineated by FDG-PET in 28 esophageal cancer patients by three radiation oncologists . The aut Muijs et al. reported that the additional use of FDG-PET led to the modification of CT-based radiotherapy planning in 57% of esophageal cancer patients . FurtherOne of the limitations in the use of PET imaging in radiotherapy planning is the low spatial resolution. Generally, the spatial resolution of current PET scanners (6–8 mm) is inferior to that of modern CT scanners (1 mm) . FurtherOther nuclides have been investigated to overcome the problems of FDG-PET. Currently, 3′-deoxy-3′-(18)F-fluorothymidine (FLT), a PET imaging marker of proliferation, has been introduced as an alternative to FDG for lung cancer . Yang et When PET is used for radiotherapy planning, a range of uncertainties related to technical, physical, biological, and analytical factors must be considered. Further investigations are warranted to establish highly accurate radiotherapy based on PET imaging for thoracic cancers.FDG-PET plays a pivotal role in accurate staging and selection of patients to be treated by radiotherapy. Furthermore, FDG-PET improves radiotherapy volume and enables dose escalation without severe side effects in lung cancer patients. The main advantage of FDG-PET for esophageal cancer patients is the detection of unrecognized lymph nodes or distal metastases. While FDG-PET was initially expected to result in more accurate target delineation, its efficacy remains controversial and delineation by FDG-PET should not be practiced in clinical use at this stage. Further studies are required to confirm the advantage of FDG-PET in radiotherapy planning for thoracic cancers.


Sulfur (S) is introduced as an additive in the growth atmosphere of carbon nanotubes (CNTs) in the range of 940-1020°C. CNT products with distorted sidewalls can be obtained by S-assisted growth. Moreover, many fascinating CNT structures can also be found in samples grown with S addition, such as bamboo-like CNTs, twisted CNTs, arborization-like CNTs, and bead-like CNTs. Compared with CNTs grown without S, more nitrogen-doping content is achieved in CNTs with S addition, which is beneficial for the properties and applications of nitrogen-doped CNTs. In addition, S can also enhance the encapsulation of ferromagnetic materials and thus improve the soft magnetic properties of CNTs, which is favorable to the applications of CNTs in the electromagnetic wave-absorbing and magnetic data storage areas. Sulfur (S) is an important additive for controlling the structures and properties of carbon nanotubes (CNTs). Many interesting carbon nanostructures, such as Y-junction CNTs , sea-urcn-type CNTs [in situ during CNT growth [Nitrogen-doping (N-doping) is an effective way to modify the properties of CNTs. Nitrogen-doped (N-doped) CNTs demonstrate negative differential resistance behavior , high elype CNTs , and impype CNTs -18. The T growth -16,19, aIn this study, S was introduced as an additive in the growth of CNTs. CNTs with distorted walls were obtained, which might be good supports for catalyst nanoparticles. Many other fascinating CNT structures were also obtained in this study's samples, such as bamboo-like CNTs, twisted CNTs, arborization-like CNTs, and bead-like CNTs. When S was used as growth promoter, the improved CNTs with high N-doping content could be achieved. In addition, the effect of S addition on enhanced soft magnetic properties of CNTs was also demonstrated.2 (300 sccm) acts as the carrier gas. In order to investigate the effect of S on CNT growth at a relatively low temperature, the temperature is set in the range of 940-1020°C. The S concentration in the catalyst (atomic ratio of S:Fe) is 1:10. CNTs without S additive are also prepared for comparison.Experimental setup and procedure are similar to that described in the previous report by the authors about N-doped CNT arrays . Ferroce8 advence). The magnetization measurements were performed on a vibrating sample magnetometer (LakeShore VSM-7307) at room temperature. Thermogravimetric analysis (TGA) results were obtained using 6-mg samples in air flow at a heating rate of 20°C/min.The resulting CNTs were characterized using scanning electron microscope , transmission electron microscope , microscopic confocal Raman spectrometer , Auger electron spectroscopy , and X-ray diffractometer  of CNTs produced at different temperatures with and without S are shown in Figure Ms of CNTs with S is enhanced by 1.5-3.5 times compared with that without S. As proved in our previous study, the Ms improvement of CNTs can be attributed to the increased encapsulation of ferromagnetic materials into their inner cavities [Ms also indicates that S can increase the encapsulation of ferromagnetic materials into CNTs.Hysteresis loops and the saturation magnetization , and the resulting Auger depth profiles of CNTs grown at 980°C with and without S are shown in Figure The XRD analysis proved the existence of pure Fe and FeCCNTs with distorted sidewalls are synthesized by the S-assisted CVD method. S is favorable to the formation of pentagon and heptagon carbon rings, and these rings are supposed to result in the formation of CNTs with distorted sidewalls. This kind of CNTs might supply more active positions for catalyst nanoparticles and have potential usage in catalyst support area. It is also found that S addition can enhance the N-doping content of CNTs, resulting from heterocyclic rings, which are favorable for the enhancement of N-doping. The effect of S on enhancing the soft magnetic properties of CNTs is also demonstrated, and the enhanced saturation magnetization can be attributed to the enhanced encapsulation of ferromagnetic material. Enhanced soft magnetic properties of CNTs are favorable for the applications of CNTs in the electromagnetic wave-absorbing and magnetic data storage areas.AES: Auger electron spectroscopy; CNTs: carbon nanotubes; CVD: chemical vapor deposition; N: nitrogen; S: sulfur; SEM: scanning electron microscope; SWCNT: single-walled CNT; TGA: thermogravimetric analysis; TEM: transmission electron microscope; XRD: X-ray diffraction.The authors declare that they have no competing interests.TC carried out the most of experiments and drafted the manuscript. RL participated in the CNT synthesis and manuscript preparation. ZH participated in the analysis of Raman and XRD spectra. FK designed the experiments and revised the manuscript. KW and DW discussed and analyzed the experimental results. All authors read and approved the final manuscript.


Preventing stroke after coronary artery bypass grafting (CABG) remains a therapeutic goal, due in part to the lack of identifiable risk factors. The aim of this study, accordingly, was to identify risk factors in CABG patients with a previous history of stroke.Patients with a history of stroke who underwent CABG at Beijing An Zhen hospital from January 2007 to July 2010 were selected (n = 430), and divided into two groups according to the occurrence of postoperative stroke. Pre-operative and post-operative data were retrospectively collected and analyzed by univariate and multivariate logistic regression analyses.Thirty-two patients (7.4%) suffered post-operative stroke. Univariate analysis identified several statistically significant risk factors in the post-operative stroke group, including pre-surgical left ventricular ejection fractions (LVEF) ≤50%, on-pump surgery, post-operative atrial fibrillation (AF), and hypotension. Multivariable analysis identified 4 independent risk factors for recurrent stroke: unstable angina (odds ratio (OR) = 2.95, 95% CI: 1.05-8.28), LVEF ≤50% , AF , and hypotension .Unstable angina, LVEF ≤50%, post-operative AF, and post-operative hypotension are independent risk factors of recurrent stroke in CABG patients with a previous history of stroke. Coronary artery bypass grafting (CABG) is an effective surgical therapy for coronary artery disease (CHD). However, the occurrence of stroke after CABG remains one of the most detrimental complications . Due to The reported incidence of stroke after CABG ranges from 1 to 5% . The occMultiple published studies have focused on post-operative stroke, but studies on post-operative stroke in patients with a previous history of stroke have not been reported. In this study, data of 430 patients with a history of stroke that underwent CABG at our hospital were retrospectively collected and analyzed to establish the independent risk factors for this patient population.Four hundred and thirty-two patients with a history of stroke were selected from 6782 patients that underwent CABG at our hospital between January 2007 and July 2010. Inclusion criteria included: patients with a history of stroke that underwent either on-pump or off-pump CABG. Exclusion criteria included: patients that underwent CABG but had no previous history of stroke, patients that underwent CABG accompanied by another cardiac surgery; or patients with the history of hemorrhagic stroke prior to surgery.A standardized anesthetic protocol was employed using intravenous high-dose fentanyl, propofol and muscle relaxant (pipecuronium), combined with inhalation sevoflurane anesthesia during the operation. Moderate systemic hypothermia and intermittent antegrade cold blood cardioplegia were adopted for some patients . Roller pump and membrane oxygenation was utilized in extracorporeal circulation. Acid-base balance was adjusted according to the α homeostasis principle. The database variables in our study comprised general information, including history of illness, cigarette and alcohol use, admitting diagnosis, laboratory examination, echocardiogram analysis, neuroimaging test results and surgery information , and stroke). All patients were in observation until their discharge. The carotid ultrasound data was limited, and was not included in our study.Stroke was defined as a focal neurologic deficit and supported by a combination of residual deficits on physical examination, radiologic abnormality on computed tomography (CT) scan or magnetic resonance imaging (MRI) and documentation in the patient's medical records. The diagnosis of post-operative stroke was initially made by the surgical team and confirmed by the neurologist, based on the clinical findings and the brain imaging pictures. All imaging studies were read by staff radiologists. Early stroke was defined as stroke occurring during surgery or within 24 hours after surgery, while late stroke was defined as stroke occurring from 24 hours after surgery until day 10 post-surgery. Post-operative hypotension was defined as systolic pressure below 90 mmHg for at least 30 min, which occurred during the time period from 24 hours until 10 days after the operation.Statistical analyses were performed with the Statistical Package for the Social Sciences (SPSS) 11.5 software. Data were presented as mean values ± standard deviation. Univariate analysis was conducted using the chi-square test for categorical data and the t-test for measurement data. Two-tailed p-values < 0.05 were considered statistically significant. Multivariate analysis was conducted using stepwise logistic regression and considered all predictors that were significantly associated.A total of 430 patients were included in the study. Post-operative stroke occurred in 32 patients (7.4%). Patients were divided into two groups according to the occurrence of post-operative stroke. Univariate analysis showed no significant difference in the following variables: age, sex, body mass index, history of hypertension, diabetes, lipid abnormality, atrial fibrillation, myocardial infarction, unstable angina, percutaneous transcoronary angioplasty, peripheral vascular disease, chronic obstructive pulmonary diseases, or cigarette and alcohol use. The post-operative stroke group showed a higher prevalence of EF≤50% than the control group . No difference was found between the groups for the number of bypasses Table .Post-operative stroke occurred in four patients in the first 24 hours after operation, in 26 patients from 24 hours until 7 days after the operation, and in two patients after the seventh day. Only one out of 28 patients 3.6%) who underwent off-pump CABG experienced an early stroke event. Three out of four patients (75%) who underwent on-pump CABG experienced an early stroke event. These differences were significantly different (p < 0.05) Multivariate analysis identified four risk factors for post-operative stroke, including: unstable angina pectoris (UAP), LVEF≤50%, post-operative AF, and hypotension . The events can be divided into early stroke and late stroke, according to the time that stroke occurred after surgery. In our study, four patients suffered early stroke, and three of them underwent on-pump CABG. Peel and colleagues found that on-pump CABG showed a higher incidence of early stroke, and off-pump CABG showed a higher incidence of late stroke, which is similar with the results of our study .The risk factors of post-operative stroke can be categorized into pre-operative, intra-operative, and post-operative factors. Pre-operative factors include advanced age, atherosclerosis in ascending aorta, unstable angina, hypertension and history of stroke; Intra-operative factors include the endurance of extracorporeal circulation and aorta clamping, or operation type. Post-operative factors include AF, micro-embolism detachment, and hypotension ,13. Our The incidence of post-operative AF is 5%-40%, and in off-pump CABG it has been shown to occur at incidences ranging from 0 to 26% ,15. WhilCurrently, the interaction between embolism and hypoperfusion is generally considered to be a major cause of post-operative stroke. Hypoperfusion may contribute to embolus retention. Several studies have found multiple emboli in the cortical watershed of patients who died after cardiac surgery, which confirms the synergistic effect of hypoperfusion and embolism on postoperative stroke. Our study suggests that unstable angina, LVEF≤50%, and hypotension are risk factors of post-operative recurrent stroke. All of these factors decrease brain perfusion, leading to stroke. Because the cerebral arteriosclerosis of patients with a history of stroke are more severe than patients without stroke, most of these patients progress to artery stenosis, where a relatively higher blood pressure is needed to maintain cerebral perfusion. When mean arterial pressure decreases 10 mmHg, the incidence of cortical watershed infarction increases by four-fold .In pre-infarction period that occurs before stroke, cerebral circulation reserve cannot compensate for the hypoperfusion status, and this decompensation stage may last for several years. This stage often manifests with headache and difficulty in speaking. . PatientAfter excluding on-pump patients, multivariate analysis eliminated both UAP and LVEF≤50% from the list of risk factors for post-operative stroke. This suggests that myocardial ischemia and cardiac function may play an important role in post-operative recurrent stroke for on-pump patients, while it influences less those patients that are off-pump. However, due to the limited number of on-pump patients, this concept should be studied in a larger clinical trial.In conclusion, patients with a history of stroke who undergo CABG are often relatively older and have more complicated co-morbidities. Since our study is a retrospective study, information such as the extent of intracranial and extracranial arteriostenosis is lacking. Future studies, especially prospective studies, are needed to determine the optimum therapeutic strategy for preventing the occurrence of post-operative stroke in patients with a history of stroke. Based on our results, strategies that focus on patients with unstable angina, LVEF≤50% and hypotension may provide improved outcomes.The authors declare that they have no competing interests.LC was responsible for the study design, data collection, statistical analysis, data interpretation, and drafting the manuscript. QL was responsible for data collection. QB was responsible for drafting the manuscript and revising it critically for important content. QJY was responsible for the study design and the final approval of article. All authors read and approved the final manuscript.


The eukaryotic cell has an intricate architecture with compartments and substructures dedicated to particular biological processes. Knowing the subcellular location of proteins not only indicates how bio-processes are organized in different cellular compartments, but also contributes to unravelling the function of individual proteins. Computational localization prediction is possible based on sequence information alone, and has been successfully applied to proteins from virtually all subcellular compartments and all domains of life. However, we realized that current prediction tools do not perform well on partial protein sequences such as those inferred from Expressed Sequence Tag (EST) data, limiting the exploitation of the large and taxonomically most comprehensive body of sequence information from eukaryotes.We developed a new predictor, TESTLoc, suited for subcellular localization prediction of proteins based on their partial sequence conceptually translated from ESTs (EST-peptides). Support Vector Machine (SVM) is used as computational method and EST-peptides are represented by different features such as amino acid composition and physicochemical properties. When TESTLoc was applied to the most challenging test case (plant data), it yielded high accuracy (~85%).http://megasun.bch.umontreal.ca/~shenyq/TESTLoc/TESTLoc.htmlTESTLoc is a localization prediction tool tailored for EST data. It provides a variety of models for the users to choose from, and is available for download at  In eukaryotes, the majority of proteins are encoded in the nuclear genome and translated on ribosomes in the cytosol. Proteins are then transported to different subcellular locations, such as the nucleus, mitochondria, chloroplasts, peroxisomes, etc., where they perform their particular roles in various biological processes. Knowledge of subcellular location is an important asset in the annotation of newly discovered proteins, as it bears clues about a protein's function. Further, knowing the location of proteins and their molecular function allows us to infer where in the cell the corresponding biological process takes place, what the physiological role of this process may be, and how the various processes are spatially integrated. Finally, information on the makeup of proteomes from bacteria-derived organelles (mitochondria and chloroplasts) helps to elucidate the migration of protein-coding genes from the endosymbiont to the host.in silico.A variety of experimental approaches are available today for identifying the subcellular localization of proteins, for example, co-expression of fluorescent proteins ,2, immunCan localization of a protein be confidently inferred via finding a homolog of known location by BLAST ? A previin silico protein localization prediction based on annotation or solely the sequence of proteins  data available, and it is unlikely that their genomes will be sequenced soon [ced soon . . When aFinally BLAST, which we showed above to be unsuited for localization prediction of full-length proteins, is equally unsuited on EST-peptide data. Even at sequence identity levels above 90%, the class-averaged accuracy for plant ESTs was below 75% .We used two datasets: data from all plants to build and evaluate the localization prediction models (input data: EST-peptides), and Arabidopsis proteins localized in nine subcellular compartments: chloroplasts (chl), cytosol (cyt), endoplasmic reticulum (end), extracellular space (ext), mitochondria (mit), nucleus (nuc), peroxisomes (per), plasma membrane (pla), and vacuole (vac). Protein sequences were selected by the following criteria: 1) they are encoded by the nuclear genome; 2) their subcellular localization is experimentally verified; and 3) the localization annotation is unambiguous . These are strict criteria in order to avoid false positives in the dataset. No bias was detected as to the functional categories of proteins collected this way compared to other studies [From SWISSPROT, we collected full-length  studies  . These combined with the above described Arabidopsis dataset constitute the plant dataset (826 sequences), which was then used to build the expanded plant dataset as specified in the following.Using the same procedure as described above for Machine learning schemes perform better when trained with larger datasets. But in practice, the size of training data is often limited by their availability. We noticed that in our initial collection of EST-peptides, a number of proteins with known subcellular location were absent, because they have no corresponding EST sequences in public databases. To construct a training set with optimal coverage, the missing EST-peptides were substituted by artificial ones, generated by breaking up full-length proteins into overlapping pieces of ~200 residues. In this way, we almost tripled the size of training data. The procedure is described below.The collected full-length protein sequences from plants were processed according to the following rules Figure :(1) When a sequence was shorter than 200 residues, it remained unchanged.(2) When a sequence was 200 to 400 residues long, fragments of length ranging from 140 to 260 residues were generated from both the N-terminus and C-terminus. The range was based on a survey of the length distribution of ESTs, which revealed a mean of ~600 nt with a standard deviation of ~180 nt. The N-terminal fragment started within 80 residues from the first methionine, and the C-terminal fragment ended at the last amino acid. This simulated the nature of ESTs, which usually contain the complete C-terminal, but lack the N-terminal region.(3) When a sequence was longer than 400 residues, an additional central fragment was generated starting anywhere downstream of the first 80 residues, but before the middle position of the original sequence.The fragmented protein sequences were combined with EST-derived peptides and clustered by CD-hit  using a threshold of 60%. The final dataset contains sequences from 41 species.We collected the best-performing localization prediction tools: TargetP, Protein Prowler, BaCelLo, Wolf-PSORT, YLoc, KnowPred, and MultiLoc2 (see Introduction), and tested their performance on the expanded plant dataset. The results of Wolf-POSRT and MultiLoc2 were obtained from a locally installed version. The prediction of YLoc was provided by its author. For the remaining tools, the results were obtained from their corresponding web-server.To assess how BLAST performs for localization prediction of ESTs, the EST data were blasted against proteins in SWISSPROT, and the localization information of the second match  is transferred to the ESTs.http://www.genome.jp/dbget-bin/show_man?aaindex)). The database currently contains 494 features for each amino acid . For each amino acid feature, its value was added up for the whole sequence, and was normalized by the sequence length. Subsequently, each EST-peptide was converted into a 494-dimension vector.Physicochemical properties of amino acids in a protein can be represented by amino acid indices , di-peptides (2nd order), tri-peptides (3rd order), tetra-peptides (4th order), penta-peptides (5th order), and hexa-peptides (6th order) in the input sequence.Six different types of amino acid composition were calculated. These include the frequency of individual amino acids  separated by x residues, x being the gap length. We experimented with gap lengths from 1 to 6.i, xj) = exp(-γ||xi-xj||2), γ>0), which requires the selection of the kernel parameter γ, and the penalty parameter C. To obtain the optimal parameters and to evaluate the predictions, we performed a 10-fold cross validation scheme for SVM parameter (C and γ) selection, followed by a 10-fold independent evaluation to assess the prediction performance , specificity (SP), positive predictive value (PPV), and Matthews Correlation Coefficient (MCC) of each individual class as follows:i: the i-th class; n: total number of classesFor each class i:TP: true positives; FP: false positives; TN: true negatives; FN: false negativesArabidopsis genomic and mRNA data collected from the European Molecular Biology Laboratory (EMBL) Nucleotide Sequence Database [Prot4EST  was usedDatabase . The mRNDatabase .We experimented with different sequence features to represent EST-peptides in SVM-based prediction of subcellular localization. As detailed in the Methods section, features included amino acid composition, grouped amino acid composition reflecting the physicochemical properties, gapped amino acid composition capturing the spatial context, as well as combinations thereof. The performance of the obtained prediction schemes varies considerably as shown below.th order amino acid composition  are underrepresented, because data from these locations are still scarce. We included these classes because in practice, a query sequence could be from any of these locations. Were these locations left out, the predictor would inevitably misassign query sequences from these three classes. Yet, when these locations are included in the predictor, there is at least the possibility that the query sequence will be correctly assigned, even if the prediction accuracy may be low (20-50%). Eventually, this shortcoming will be alleviated when more data from these locations become available.Previous studies showed that integration of multiple sequence features improves the performance of localization prediction ,32,34. WIntegration of prediction results from individual features was achieved by a two-layer SVM Figure . The firth order amino acid composition, 6th order group-C composition and 7th order group-D composition), as well as the predictions from these features. Again, these schemes showed a similar MCC as the predictors based on a single feature, but with lower sensitivity and higher positive predictive value for most classes . In addition, ESTs are products of single-pass reads often containing low quality regions with sequencing errors that further complicate the task. Several tools have been developed for ORF identification in EST sequences ,54,56. WWe built a tool named TESTLoc that combines EST translation with localization prediction. TESTLoc has two components. The first takes EST nucleotide sequences as input and generates EST-peptides via the tool Prot4EST. The second takes EST-peptides as input and outputs the probability that the peptide is targeted to a given subcellular compartment. The current model predicts nine locations: cytosol, endoplasmic reticulum, extracellular space, mitochondria, nucleus, peroxisomes, plasma membrane, vacuole, and chloroplasts.Arabidopsis ESTs that correspond to proteins of known localization. Sequences were represented by three best-performing features: 4th order amino acid composition, 6th order group-C amino acid composition, and 7th order group-D amino acid composition. The resulting predictions showed high MCC values (>0.6) for most classes  Note that TESTLoc is designed for EST data, and should not be applied to full-length proteins  yielded the best performance. This is unexpected for a feature space two orders of magnitude larger  than the sample size . Statistically, most tetra-peptides should be represented by only a few proteins, which should render machine learning rather ineffective. Alternatively, certain tetra-peptides may be over-represented in a given class, either due to a strong location-related signal or an artifact arising from redundancy in the dataset. To clarify the situation, we scrutinized the tetra-peptides present in our data  is 160,000, our particular dataset contains two third . About one half  of the occurring motifs are found in single classes and are present in only a few members of a given class (<3%). Further, the motifs within a class do not show conserved sequence patterns. The complementary trend applies to the absence of tetra-peptides: no particular tetra-peptide is absent from only one class. In sum, there is no notable enrichment of, or bias against, certain tetra-peptide motifs in a class, nor any sign of a data redundancy artifact.How then does this feature category achieve superior prediction performance? One possibility is that tetra-peptides bear targeting information in the form of more complex patterns such as nonadjacent correlation of multiple tetra-peptides, which we would not have recognized in our analysis.Our results described here show that the SVM machine learning method, together with sequence features carefully chosen, predicts the subcellular location of EST-derived proteins with high accuracy, thus filling the need for a tool tailored to EST data. We implemented TESTLoc as a fully automated pipeline combining EST-ORF prediction and localization prediction. This tool opens new avenues for systematic analysis of EST data from any eukaryote including challenging photosynthetic taxa such as plants.YQS developed and implemented the methods. GB conceived of the study, participated in its design, and supervised the process. YQS drafted the manuscript. Both authors read and approved the final manuscript.Influence of sequence similarity on the accuracy of localization prediction by TESTLoc and BLAST.Click here for fileList of available subcellular localization prediction methods.Click here for fileGene Ontology (GO) term of proteins from the plant dataset used in this study.Click here for fileArabidopsis ESTs corresponding to proteins of known localizationSelection of .Click here for filePerformance of predicting subcellular localization of EST-derived proteins, based on each sequence feature .Click here for fileThe independent evaluation of SVM predictors based on different representations of amino acid composition, measured with sensitivity and positive predictive value.Click here for fileAccuracy of ESTScan for the prediction of start/stop positions of coding regions in EST sequences.Click here for fileComparison of prediction performance of available tools and TESTLoc on full-length plant protein sequences.Click here for fileTetra-peptides present in the expanded plant ESTs data.Click here for file


Complete Genomics provides an open-source suite of command-line tools for the analysis of their CG-formatted mapped sequencing files. Determination of; for example, the functional impact of detected variants, requires annotation with various databases that often require command-line and/or programming experience; thus, limiting their use to the average research scientist. We have therefore implemented this CG toolkit, together with a number of annotation, visualisation and file manipulation tools in Galaxy called CGtag .In order to provide research scientists with web-based, simple and accurate analytical and visualisation applications for the selection of candidate mutations from Complete Genomics data, we have implemented the open-source Complete Genomics tool set, CGATools, in Galaxy. In addition we implemented some of the most popular command-line annotation and visualisation tools to allow research scientists to select candidate pathological mutations . Furthermore, we have developed a cloud-based public Galaxy instance to host the CGtag toolkit and other associated modules.CGtag provides a user-friendly interface to all research scientists wishing to select candidate variants from CG or other next-generation sequencing platforms’ data. By using a cloud-based infrastructure, we can also assure sufficient and on-demand computation and storage resources to handle the analysis tasks. The tools are freely available for use from an NBIC/CTMM-TraIT  cloud-based Galaxy instance, or can be installed to a local (production) Galaxy via the NBIC Galaxy tool shed. Complete Genomics (CG) supplies results for whole-genome next-generation sequencing (NGS) data mapped to a user-defined genome  and addiThis implementation of the CGATools in a Galaxy environment simplifies the analysis of genomes via the Galaxy GUI and the cloud resource ensures that sufficient computing power is available for the analysis. The inherent functionality in Galaxy of CGtag enables the creation of customisable user-defined workflows by the scientist and not only by the bioinformatician.For large datasets, transfer to Galaxy via SFTP is available and recommended, but is still limited by the upload speed of the user’s internet connection, and can be a bottleneck in the analysis of large datasets.CGATools is an open-source project to provide tools for downstream analysis of Complete Genomics data, and may be downloaded from their repository . These tTo provide users with enhanced filtering capabilities, we have integrated several command-line annotation tools in this NBIC/CTMM-TraIT Galaxy instance. ANNOVAR  is a comA generic genomic data plotter tool based on GNUplot is available, which takes as input, a tab-delimited file of format chr–start-end–value, and will output either a single chromosome plot, an overview of all chromosome plots in a single image, or a sub-region of a chromosome defined by the user. Additionally, the tool has the option of plotting input from a second file in the same image, which is useful for tumour-normal comparison Figure . B-allelTo support fusion gene analysis we have created a custom Circos tool which uses CG files, CG junctions file and CG varfile for NGS, and the results from SNP arrays analysis, specifically the B-allele frequency (BAF) and copy number variation (CNV) files. The output is either a whole-genome plot, per-chromosome plots, a single image containing all the per-chromosome plots together, or a plot of a custom region defined by the user . Additionally the user can select an “impacted genes” track for the per-chromosome plots, which will print the names of the genes impacted by SV events along the outer edge of the image Figure . This cuIn addition to these tools within Galaxy, structural variation files processed using CGtag may be exported to our previously described fusion gene prioritisation tool, iFUSE  to identOur suite of tools also includes several auxiliary tools supplied by CG but not available from the Galaxy tool shed which offer the user several file format conversion tools Table  that enaNBIC Galaxy is hosted at a high performance computing (HPC) cloud system operated by SURFsara . This HPThe second contribution of Cloudman to our NBIC Galaxy system is its ability to set up a flexible virtual cluster and ability to provide auto-scaling support. The previous NBIC Galaxy was hosted on a dedicate physical server with rather limit resources . Due to this resource limitation, our NBIC Galaxy was never promoted to be a real data analysis server to handle the production level of NGS datasets. On the other hand, because of the sporadic nature of user access, the server was mostly on idle during its 2-year lifespan. Moving to Cloud resolved both issues. The current NBIC Galaxy operates on top of a virtual cluster. This virtual cluster contains one head node and a number of worker nodes. These nodes are all virtual machines that are built using the machine image generated by the Cloudman script. During minimal usage, the cluster will only contain one head node. Once a significant load occurs due to training courses or production level data analysis, the virtual cluster can automatically scale itself upwards. More worker nodes will be added dynamically to this virtual cluster to boost the capacity of NBIC Galaxy. Once the load decreases, the virtual cluster can scale down again to operate with only a limited number of nodes.The use of shared resources does have drawback as well. We have experienced a more obvious I/O bottleneck in the cloud-based NBIC Galaxy compared to the previous system that ran in a physical machine. In the HPC Cloud, storage is provided through a network file system (NFS) instead of a local hard disk. When more concurrent Cloud users are using the Cloud resource, we observe the extra job time caused by I/O delays. However, we argue that this issue is far outweighed by the benefit of having a dynamic virtual cluster support to the NBIC Galaxy.Project Name: CGtag: Complete Genomics Toolkit and Annotation in a Cloud-based Galaxy Project home page:http://galaxy.ctmm-trait.nlOperating system: Linux Programming language: Python , R (CGtag), Bash (CGTag) Other requirements: Circos [License: GPL v3Restrictions to use by non-academics: ANNOVAR license must be obtained before it can be used.Galaxy resources: published page: http://galaxy.ctmm-trait.nl/u/saskia-hiltemann/p/cgtag Links to tool shed repositories:annovar: http://toolshed.nbic.nl/view/saskia-hiltemann/annovar cgatools: http://toolshed.nbic.nl/view/saskia-hiltemann/cgatools\_v17 circos plotters: http://toolshed.nbic.nl/view/saskia-hiltemann/cg\_circos\_plots condel: http://toolshed.nbic.nl/view/saskia-hiltemann/condel file manipulation tools: http://toolshed.nbic.nl/view/saskia-hiltemann/file\_manipulation generic genomic data plotter: http://toolshed.nbic.nl/view/saskia-hiltemann/genomic\_data\_plotter mutation assessor: http://toolshed.nbic.nl/view/saskia-hiltemann/mutation\_assessor NOTE: these tools can be installed to both Cloudman Galaxy instances or non-Cloudman Galaxy instances alike .: Circos , GNUplot: Circos , Complet: Circos  and depehttp://galaxy.ctmm-trait.nl) and the NBIC Galaxy tool shed (http://toolshed.nbic.nl).All tools described, as well as example data, are available from the NBIC/CTMM-TraIT Galaxy server (BAF: B-Allele frequency; CG: Complete genomics; CGATools: Complete genomics analysis tools; CGtag: Complete genomics toolkit and annotation in a cloud-based galaxy; NBIC: The Netherlands Bioinformatics Center; NFS: Network file system; NGS: Next generation sequencing; SNV: Single nucleotide variation; SV: Structural variation.The authors declare that they have no competing interests.SH, GJ, HM and AS contributed to the design and coordination of CGtag and manuscript preparation. SH, MdH, IP and HM contributed to implementing CGtag. SH, GJ, PvdS and AS contributed to testing of CGtag. MdH and HM implemented Galaxy Cloudman for the SURFsara/Big-grid HPC cloud. All authors read and approved the final manuscript.


Cow's milk, egg, wheat, soy, peanut, and fish account for about 90% of the food allergies but there are considerable differences from one country to another. Milk allergy is among the best characterized food allergies, particularly in infants and small children. Only part of the children with early allergy to cow's milk grow into shool-age with milk allergy but those that do often have severe symptoms and high specific IgE level to milk. In accordance, attaining tolerance to cow's milk is associated with decreased epitope binding by IgE and a concurrent increase in corresponding epitope binding by IgG4. Recent data point that analysis of IgE response to milk components may help in determining those with higher risk for persistent or more severe milk allergy.Among wheat allergic patients, co-sensitization to cow's milk and hen's egg is common. Wheat ingestion may trigger immunoglobulin E (IgE)-mediated immediate symptoms, including urticaria, angioedema, bronchial obstruction, nausea and abdominal pain, or in severe cases, even systemic anaphylaxis. Delayed reactions include gastrointestinal symptoms and worsen-ing of atopic dermatitis. In addition to food allergy, wheat ingestion may cause exercise-induced anaphylaxis, or celiac disease (CD), and inhalation and handling of wheat flour aller-gens may lead to respiratory allergy, or contact urticaria on the skin.Wheat IgE is commonly found in all ages of atopic children when whole grains are used as an antigen either in skin prick tests or serum IgE measurements. The specificity of this IgE re-sponse in identifying clinical disease, however, is poor. It is of importance to recognize dis-ease-determining components in the IgE response. Several studies have shown that sensiti-zation particularly to omega-5 gliadin is associated with challenge-proven wheat-allergy. Moreover, recent data imply that gliadin-positive patients have more likely severe reactions after wheat ingestion. A well-characterized severe clinical entity is also wheat-dependent, ex-ercise-induced anaphylaxis in which sensitization to omega-5 gliadin is a prerequisite.We have analyzed especially the gliadin-sepcific responses in wheat allergy. Sensitization to gliadin with a SPT wheal of ≥5 mm at the time of the diagnostic challenge was associated with a slower course of recovery from wheat hypersensitivity (p = 0.019), and a SPT wheal of ≥ 3 mm to gliadin at any time was associated with the development of asthma. Recently, we examined IgE response to 22 wheat components in children with challenge positive wheat allergy and their controls. The results show that wheat-allergy diagnosis can be improved considerably by component-based ap-proach. In the future, wheat IgE diagnosis should include at least measurement of IgE to gli-adins.Gluten and its major component, gliadin, is essential also in the pathogenesis of celiac dis-ease. Gliadin can be a target of both cellular and humoral immune responses. Approximately 90 percent of patients with celiac disease have the HLA-DQ2 haplotype, explaining the family-association of the disease but still leaving open the wide variability in prevalence between dif-ferent Caucasian populations. Both IgA and IgG antibodies can be seen in CD patients but the most sensitive diagnostic work-up is to define tissue transglutaminase (tTG) transglutami-nase IgA antibodies.