Automatic Prediction of Recurrence of Major Cardiovascular Events: A Text Mining Study Using Chest X-Ray Reports

Background and Objective. Electronic health records (EHRs) contain free-text information on symptoms, diagnosis, treatment, and prognosis of diseases. However, this potential goldmine of health information cannot be easily accessed and used unless proper text mining techniques are applied. The aim of this project was to develop and evaluate a text mining pipeline in a multimodal learning architecture to demonstrate the value of medical text classification in chest radiograph reports for cardiovascular risk prediction. We sought to assess the integration of various text representation approaches and clinical structured data with state-of-the-art deep learning methods in the process of medical text mining. Methods. We used EHR data of patients included in the Second Manifestations of ARTerial disease (SMART) study. We propose a deep learning-based multimodal architecture for our text mining pipeline that integrates neural text representation with preprocessed clinical predictors for the prediction of recurrence of major cardiovascular events in cardiovascular patients. Text preprocessing, including cleaning and stemming, was first applied to filter out the unwanted texts from X-ray radiology reports. Thereafter, text representation methods were used to numerically represent unstructured radiology reports with vectors. Subsequently, these text representation methods were added to prediction models to assess their clinical relevance. In this step, we applied logistic regression, support vector machine (SVM), multilayer perceptron neural network, convolutional neural network, long short-term memory (LSTM), and bidirectional LSTM deep neural network (BiLSTM). Results. We performed various experiments to evaluate the added value of the text in the prediction of major cardiovascular events. The two main scenarios were the integration of radiology reports (1) with classical clinical predictors and (2) with only age and sex in the case of unavailable clinical predictors. In total, data of 5603 patients were used with 5-fold cross-validation to train the models. In the first scenario, the multimodal BiLSTM (MI-BiLSTM) model achieved an area under the curve (AUC) of 84.7%, misclassification rate of 14.3%, and F1 score of 83.8%. In this scenario, the SVM model, trained on clinical variables and bag-of-words representation, achieved the lowest misclassification rate of 12.2%. In the case of unavailable clinical predictors, the MI-BiLSTM model trained on radiology reports and demographic (age and sex) variables reached an AUC, F1 score, and misclassification rate of 74.5%, 70.8%, and 20.4%, respectively. Conclusions. Using the case study of routine care chest X-ray radiology reports, we demonstrated the clinical relevance of integrating text features and classical predictors in our text mining pipeline for cardiovascular risk prediction. The MI-BiLSTM model with word embedding representation appeared to have a desirable performance when trained on text data integrated with the clinical variables from the SMART study. Our results mined from chest X-ray reports showed that models using text data in addition to laboratory values outperform those using only known clinical predictors

Genomic and proteomic biases inform metabolic engineering strategies for anaerobic fungi.

Anaerobic fungi (Neocallimastigomycota) are emerging non-model hosts for biotechnology due to their wealth of biomass-degrading enzymes, yet tools to engineer these fungi have not yet been established. Here, we show that the anaerobic gut fungi have the most GC depleted genomes among 443 sequenced organisms in the fungal kingdom, which has ramifications for heterologous expression of genes as well as for emerging CRISPR-based genome engineering approaches. Comparative genomic analyses suggest that anaerobic fungi may contain cellular machinery to aid in sexual reproduction, yet a complete mating pathway was not identified. Predicted proteomes of the anaerobic fungi also contain an unusually large fraction of proteins with homopolymeric amino acid runs consisting of five or more identical consecutive amino acids. In particular, threonine runs are especially enriched in anaerobic fungal carbohydrate active enzymes (CAZymes) and this, together with a high abundance of predicted N-glycosylation motifs, suggests that gut fungal CAZymes are heavily glycosylated, which may impact heterologous production of these biotechnologically useful enzymes. Finally, we present a codon optimization strategy to aid in the development of genetic engineering tools tailored to these early-branching anaerobic fungi

Polymer refilling of presbyopic human lenses in vitro restores the ability to undergo accommodative changes

PURPOSE. Because presbyopia is thought to be accompanied by increased lens sclerosis this study was conducted to investigate whether refilling the capsule of the presbyopic human lens with a soft polymer would restore the ability of the lens to undergo accommodative changes. METHODS. Accommodative forces were applied to natural and refilled lenses by circumferential stretching through the ciliary body and zonular complex. Nine natural lenses and 10 refilled lenses from donors ranging in age from 17 to 60 years were studied. Two refill polymers with a different Young's modulus were used. The lens power was measured by a scanning laser ray-tracing technique, and lens diameter and lens thickness were measured simultaneously while the tension on the zonules was increased stepwise by outward pull on the ciliary body. RESULTS. In the natural lenses the older lenses were not able to undergo power changes with stretching of the ciliary body, whereas in the refilled lenses, all lenses showed power changes comparable to young, natural lenses. The refilled human lenses had a higher lens power than the age-matched natural lenses. The Young's modulus of the polymers influenced the lens power change when measured with the ciliary body diameter increased by 4 Him. CONCLUSIONS. Refilling presbyopic lenses with a soft polymer enabled restoration of lens power changes with mechanical stretching. Because sclerosis of the lens is an important factor in human presbyopia, refilling the lens during lens surgery for cataract could enable restoration of clear vision and accommodation in human presbyopia

Dietary treatment in Dutch children with phenylketonuria:An inventory of associated social restrictions and eating problems

OBJECTIVES: Dietary treatment in phenylketonuria (PKU) is known to cause eating problems, but knowledge of both prevalence and magnitude, especially for social restrictions, is scarce. Our aim was to evaluate the social restrictions and eating problems that children with PKU and their caregivers experience with dietary treatment. METHODS: A web-based questionnaire, based on the Behavioral Pediatrics Feeding Assessment Scale with additional PKU-specific questions, was developed in close collaboration with and distributed by the Dutch PKU Association, which sent an e-mail to its members containing a link to the questionnaire. The questionnaire was completed by caregivers of children with PKU in the Netherlands and caregivers of age-matched children without PKU. Data were analyzed with the Kruskal-Wallis and Mann-Whitney U test using SPSS. RESULTS: Compared with caregivers of children in the control group (ages 1-16 y; n = 50), caregivers of children with PKU (ages 1-16 y; n = 57) reported more difficulty in offering food variety, experienced more stress when eating an evening meal outside the home and during vacation, and were stricter about (accidental) spilling of food during dinner by the child (P < 0.05). They also reported to being angrier, more frustrated, and more anxious when feeding their child, and they more often felt that their child's eating pattern had a negative influence on the child's general health (P < 0.05). CONCLUSION: This pilot study provides further evidence that restriction of social activities and eating problems associated with dietary restrictions is more common in children with PKU, and warrants awareness on this topic among professionals working with these children

Early-branching gut fungi possess a large, comprehensive array of biomass-degrading enzymes

The fungal kingdom is the source of almost all industrial enzymes in use for lignocellulose bioprocessing. We developed a systems-level approach that integrates transcriptomic sequencing, proteomics, phenotype, and biochemical studies of relatively unexplored basal fungi. Anaerobic gut fungi isolated from herbivores produce a large array of biomass-degrading enzymes that synergistically degrade crude, untreated plant biomass and are competitive with optimized commercial preparations from Aspergillus and Trichoderma. Compared to these model platforms, gut fungal enzymes are unbiased in substrate preference due to a wealth of xylan-degrading enzymes. These enzymes are universally catabolite-repressed and are further regulated by a rich landscape of noncoding regulatory RNAs. Additionally, we identified several promising sequence-divergent enzyme candidates for lignocellulosic bioprocessing

Genetic susceptibility loci for cardiovascular disease and their impact on atherosclerotic plaques

Background: Atherosclerosis is a chronic inflammatory disease in part caused by lipid uptake in the vascular wall, but the exact underlying mechanisms leading to acute myocardial infarction and stroke remain poorly understood. Large consortia identified genetic susceptibility loci that associate with large artery ischemic stroke and coronary artery disease. However, deciphering their underlying mechanisms are challenging. Histological studies identified destabilizing characteristics in human atherosclerotic plaques that associate with clinical outcome. To what extent established susceptibility loci for large artery ischemic stroke and coronary artery disease relate to plaque characteristics is thus far unknown but may point to novel mechanisms. Methods: We studied the associations of 61 established cardiovascular risk loci with 7 histological plaque characteristics assessed in 1443 carotid plaque specimens from the Athero-Express Biobank Study. We also assessed if the genotyped cardiovascular risk loci impact the tissue-specific gene expression in 2 independent biobanks, Biobank of Karolinska Endarterectomy and Stockholm Atherosclerosis Gene Expression. Results: A total of 21 established risk variants (out of 61) nominally associated to a plaque characteristic. One variant (rs12539895, risk allele A) at 7q22 associated to a reduction of intraplaque fat, P=5.09×10−6 after correction for multiple testing. We further characterized this 7q22 Locus and show tissue-specific effects of rs12539895 on HBP1 expression in plaques and COG5 expression in whole blood and provide data from public resources showing an association with decreased LDL (low-density lipoprotein) and increase HDL (high-density lipoprotein) in the blood. Conclusions: Our study supports the view that cardiovascular susceptibility loci may exert their effect by influencing the atherosclerotic plaque characteristics