Novel micelle PCR-based method for accurate, sensitive and quantitative microbiota profiling

In the last decade, many researchers have embraced 16S rRNA gene sequencing techniques, which has led to a wealth of publications and documented differences in the composition of microbial communities derived from many different ecosystems. However, comparison between different microbiota studies is currently very difficult due to the lack of a standardized 16S rRNA gene sequencing protocol. Here we report on a novel approach employing micelle PCR (micPCR) in combination with an internal calibrator that allows for standardization of microbiota profiles via their absolute abundances. The addition of an internal calibrator allows the researcher to express the resulting operational taxonomic units (OTUs) as a measure of 16S rRNA gene copies by correcting the number of sequences of each individual OTU in a sample for efficiency differences in the NGS process. Additionally, accurate quantification of OTUs obtained from negative extraction control samples allows for the subtraction of contaminating bacterial DNA derived from the laboratory environment or chemicals/reagents used. Using equimolar synthetic microbial community samples and low biomass clinical samples, we demonstrate that the calibrated micPCR/NGS methodology possess a much higher precision and a lower limit of detection compared with traditional PCR/NGS, resulting in more accurate microbiota profiles suitable for multi-study comparison

Micelle PCR reduces chimera formation in 16S rRNA profiling of complex microbial DNA mixtures

16S rRNA gene profiling has revolutionized the field of microbial ecology. Many researchers in various fields have embraced this technology to investigate bacterial compositions of samples derived from many different ecosystems. However, it is important to acknowledge the current limitations and drawbacks of 16S rRNA gene profiling. Although sample handling, DNA extraction methods and the choice of universal 16S rRNA gene PCR primers are well known factors that could seriously affect the final results of microbiota profiling studies, inevitable amplification artifacts, such as chimera formation and PCR competition, are seldom appreciated. Here we report on a novel micelle based amplification strategy, which overcomes these limitations via the clonal amplification of targeted DNA molecules. Our results show that micelle PCR drastically reduces chimera formation by a factor of 38 (1.5% vs. 56.9%) compared with traditional PCR, resulting in improved microbial diversity estimates. In addition, compartmentalization during micelle PCR prevents PCR competition due to unequal amplification rates of different 16S template molecules, generating robust and accurate 16S microbiota profiles required for comparative studies (e.g. longitudinal surveys)

Contextual Mixture of Experts: Integrating Knowledge into Predictive Modeling

This work proposes a new data-driven model devised to integrate process knowledge into its structure to increase the human-machine synergy in the process industry. The proposed Contextual Mixture of Experts (cMoE) explicitly uses process knowledge along the model learning stage to mold the historical data to represent operators' context related to the process through possibility distributions. This model was evaluated in two real case studies for quality prediction, including a sulfur recovery unit and a polymerization process. The contextual mixture of experts was employed to represent different contexts in both experiments. The results indicate that integrating process knowledge has increased predictive performance while improving interpretability by providing insights into the variables affecting the process's different regimes

Assessment of insertion techniques and complication rates of dual lumen central venous catheters in patients with hematological malignancies

One hundred and twenty-three dual lumen silicone rubber central venous catheters were inserted into 101 patients with hematological malignancies undergoing intensive treatment. There was a perioperative complication rate of 13%. Open and closed techniques for inserting the catheter were compared. The operating time needed for introducing the catheter by the closed technique (average, 51 minutes) was significantly shorter (p< 0.001) than the time needed for the open technique (70 minutes), whereas complication rates were equal in both techniques. On average, the catheters functioned for 149 days. Complications leading to removal were observed in 29.3% of patients, most of which were catheter-related infections (20.4%). Thromboembolic complications leading to removal were less frequent (4.1%) and appeared significantly earlier (p<0.001). These data indicate that introduction of the catheter by direct puncture of the subclavian vein is a quick and safe technique, and that this type of catheter is suitable for long-term use, both for infusion and for blood sampling

Exposure to low-dose radiation and the risk of breast cancer among women with a familial or genetic predisposition:a meta-analysis

Women with familial or genetic aggregation of breast cancer are offered screening outside the population screening programme. However, the possible benefit of mammography screening could be reduced due to the risk of radiation-induced tumours. A systematic search was conducted addressing the question of how low-dose radiation exposure affects breast cancer risk among high-risk women. A systematic search was conducted for articles addressing breast cancer, mammography screening, radiation and high-risk women. Effects of low-dose radiation on breast cancer risk were presented in terms of pooled odds ratios (OR). Of 127 articles found, 7 were selected for the meta-analysis. Pooled OR revealed an increased risk of breast cancer among high-risk women due to low-dose radiation exposure (OR = 1.3, 95% CI: 0.9- 1.8). Exposure before age 20 (OR = 2.0, 95% CI: 1.3-3.1) or a mean of a parts per thousand yen5 exposures (OR = 1.8, 95% CI: 1.1-3.0) was significantly associated with a higher radiation-induced breast cancer risk. Low-dose radiation increases breast cancer risk among high-risk women. When using low-dose radiation among high-risk women, a careful approach is needed, by means of reducing repeated exposure, avoidance of exposure at a younger age and using non-ionising screening techniques

Data Mining in MRO

Data mining seems to be a promising way to tackle the problem of unpredictability in MRO organizations. The Amsterdam University of Applied Sciences therefore cooperated with the aviation industry for a two-year applied research project exploring the possibilities of data mining in this area. Researchers studied more than 25 cases at eight different MRO enterprises, applying a CRISP-DM methodology as a structural guideline throughout the project. They explored, prepared and combined MRO data, flight data and external data, and used statistical and machine learning methods to visualize, analyse and predict maintenance. They also used the individual case studies to make predictions about the duration and costs of planned maintenance tasks, turnaround time and useful life of parts. Challenges presented by the case studies included time-consuming data preparation, access restrictions to external data-sources and the still-limited data science skills in companies. Recommendations were made in terms of ways to implement data mining – and ways to overcome the related challenges – in MRO. Overall, the research project has delivered promising proofs of concept and pilot implementation

Data Mining in MRO

Data mining seems to be a promising way to tackle the problem of unpredictability in MRO organizations. The Amsterdam University of Applied Sciences therefore cooperated with the aviation industry for a two-year applied research project exploring the possibilities of data mining in this area. Researchers studied more than 25 cases at eight different MRO enterprises, applying a CRISP-DM methodology as a structural guideline throughout the project. They explored, prepared and combined MRO data, flight data and external data, and used statistical and machine learning methods to visualize, analyse and predict maintenance. They also used the individual case studies to make predictions about the duration and costs of planned maintenance tasks, turnaround time and useful life of parts. Challenges presented by the case studies included time-consuming data preparation, access restrictions to external data-sources and the still-limited data science skills in companies. Recommendations were made in terms of ways to implement data mining – and ways to overcome the related challenges – in MRO. Overall, the research project has delivered promising proofs of concept and pilot implementation

A Deep Learning Approach Utilizing Covariance Matrix Analysis for the ISBI Edited MRS Reconstruction Challenge

This work proposes a method to accelerate the acquisition of high-quality edited magnetic resonance spectroscopy (MRS) scans using machine learning models taking the sample covariance matrix as input. The method is invariant to the number of transients and robust to noisy input data for both synthetic as well as in-vivo scenarios

Characterization of the nasopharyngeal and middle ear microbiota in gastroesophageal reflux-prone versus gastroesophageal reflux non-prone children

Otitis media (OM) is one of the most common pediatric infections worldwide, but the complex microbiology associated with OM is poorly understood. Previous studies have shown an association between OM and gastroesophageal reflux (GER) in children. Therefore, in order to bridge the gap in our current understanding of the interaction between GER and OM, we investigated the nasopharyngeal and middle ear microbiota of children suffering from GER-associated OM and OM only, using culture-independent 16S rRNA gene sequencing. Middle ear fluid, nasopharyngeal swabs, and clinical data were collected as part of a prospective pilot study conducted at the Department of Otorhinolaryngology of the Erasmus MC-Sophia Children’s Hospital, Rotterdam, the Netherlands. A total of 30 children up to 12 years of age who suffered from recurrent acute otitis media (AOM) (5), chronic otitis media with effusion (OME) (23), or both (2), and who were listed for tympanostomy tube placement, were included in the study. Nine children were included in the GER-associated OM cohort and 21 in the OM-only cohort. We found no obvious effect of GER on the nasopharyngeal and middle ear microbiota between the two groups of children. However, our results highlight the need to assess the true role of Alloiococcus spp. and Turicella spp. in children presenting with a high prevalence of recurrent AOM and chronic OME

Development and evaluation of a culture-free microbiota profiling platform (MYcrobiota) for clinical diagnostics

Microbiota profiling has the potential to greatly impact on routine clinical diagnostics by detecting DNA derived from live, fastidious, and dead bacterial cells present within clinical samples. Such results could potentially be used to benefit patients by influencing antibiotic prescribing practices or to generate new classical-based diagnostic methods, e.g., culture or PCR. However, technical flaws in 16S rRNA gene next-generation sequencing (NGS) protocols, together with the requirement for access to bioinformatics, currently hinder the introduction of microbiota analysis into clinical diagnostics. Here, we report on the development and evaluation of an “end-to-end” microbiota profiling platform (MYcrobiota), which combines our previously validated micelle PCR/NGS (micPCR/NGS) methodology with an easy-to-use, dedicated bioinf