Open-labelled study to monitor the effect of an amino acid formula on symptom management in children with spinal muscular atrophy type I: The SMAAF pilot study.

BACKGROUND: An increasing number of families with children who have spinal muscular atrophy (SMA) are incorporating a special amino acid diet into their child's feeding regimens. Characteristics of the diet include high-carbohydrate and low-fat content with added probiotics. However, because of insufficient evidenced-based research, clinicians are unable to prescribe or endorse this diet. Our aim was to assess the tolerability of an adapted version of the traditional amino acid diet in children with SMA type I. METHODS: Children with SMA type I were recruited if they were enterally fed and experienced at least one gastrointestinal symptom (reflux, vomiting, constipation, and/or diarrhea). Children were transitioned to an amino acid formula (Neocate Syneo-Nutricia) for 8 weeks. Feeding tolerance was measured weekly by telephone consultation to monitor reflux, vomiting, stool consistency, and frequency. RESULTS: Fourteen children were recruited, the mean age was 4.1 years (±1.2 SD), and 64% of participants were female. The mean resting energy expenditure determined by indirect calorimetry was 51.5 kcal/kg (±7 SD). The most common gastrointestinal complaint before switching to the amino acid formula was constipation, which was reported in 12 of 14 (85%) patients, of which 10 of the 12 (83%) children required daily stool softeners/laxatives to help regulate bowel function. After 8 weeks on the amino acid formula, 10 out of 12 (83%) children stopped or reduced constipation medication. CONCLUSION: Children with SMA type I who display gastrointestinal symptoms such as constipation and reflux may benefit from an amino acid formula that is fortified with probiotics.

Cloud-native distributed genomic pileup operations.

MOTIVATION: Pileup analysis is a building block of many bioinformatics pipelines, including variant calling and genotyping. This step tends to become a bottleneck of the entire assay since the straightforward pileup implementations involve processing of all base calls from all alignments sequentially. On the other hand, a distributed version of the algorithm faces the intrinsic challenge of splitting reads-oriented file formats into self-contained partitions to avoid costly data exchange between computational nodes. RESULTS: Here, we present a scalable, distributed and efficient implementation of a pileup algorithm that is suitable for deploying in cloud computing environments. In particular, we implemented: (i) our custom data-partitioning algorithm optimized to work with the alignment reads, (ii) a novel and unique approach to process alignment events from sequencing reads using the MD tags, (iii) the source code micro-optimizations for recurrent operations, and (iv) a modular structure of the algorithm. We have proven that our novel approach consistently and significantly outperforms other state-of-the-art distributed tools in terms of execution time (up to 6.5× faster) and memory usage (up to 2× less), resulting in a substantial cloud cost reduction. SeQuiLa is a cloud-native solution that can be easily deployed using any managed Kubernetes and Hadoop services available in public clouds, like Microsoft Azure Cloud, Google Cloud Platform, or Amazon Web Services. Together with the already implemented distributed range join and coverage calculations, our package provides end-users with a unified SQL interface for convenient analyses of population-scale genomic data in an interactive way. AVAILABILITY AND IMPLEMENTATION: https://biodatageeks.github.io/sequila/.

Dietary management of infants and young children with feeding difficulties and unsatisfactory weight gain using a nutritionally complete hypercaloric infant formula. practical considerations from clinical cases.

INTRODUCTION: A decrease in weight velocity and feeding difficulties in infants may be caused by an inadequate caloric intake and underlying medical conditions. CASE DESCRIPTION: By focusing on four clinical cases, this article illustrates the temporary use of a special infant formula in orally-fed and enterally-fed infants with unsatisfactory weight gain and special medical conditions such as gastrointestinal and neurological disorders. The formula was a nutritionally complete hypercaloric infant formula containing partially hydrolyzed whey protein. It was used after full consideration of all feeding options including breastfeeding. CONCLUSION: Implementing appropriate feeding behaviors, adapted to age and potential comorbidities, is an essential prerequisite for therapeutic management. The use of a nutritionally complete hypercaloric infant formula can be helpful to manage unsatisfactory weight gain and feeding difficulties in infants.

SeQuiLa-cov: A fast and scalable library for depth of coverage calculations.

BACKGROUND: Depth of coverage calculation is an important and computationally intensive preprocessing step in a variety of next-generation sequencing pipelines, including the analysis of RNA-sequencing data, detection of copy number variants, or quality control procedures. RESULTS: Building upon big data technologies, we have developed SeQuiLa-cov, an extension to the recently released SeQuiLa platform, which provides efficient depth of coverage calculations, reaching >100× speedup over the state-of-the-art tools. The performance and scalability of our solution allow for exome and genome-wide calculations running locally or on a cluster while hiding the complexity of the distributed computing with Structured Query Language Application Programming Interface. CONCLUSIONS: SeQuiLa-cov provides significant performance gain in depth of coverage calculations streamlining the widely used bioinformatic processing pipelines.

Comparison of kNN and k-means optimization methods of reference set selection for improved CNV callers performance.

BACKGROUND: There are over 25 tools dedicated for the detection of Copy Number Variants (CNVs) using Whole Exome Sequencing (WES) data based on read depth analysis. The tools reported consist of several steps, including: (i) calculation of read depth for each sequencing target, (ii) normalization, (iii) segmentation and (iv) actual CNV calling. The essential aspect of the entire process is the normalization stage, in which systematic errors and biases are removed and the reference sample set is used to increase the signal-to-noise ratio. Although some CNV calling tools use dedicated algorithms to obtain the optimal reference sample set, most of the advanced CNV callers do not include this feature. To our knowledge, this work is the first attempt to assess the impact of reference sample set selection on CNV detection performance. METHODS: We used WES data from the 1000 Genomes project to evaluate the impact of various methods of reference sample set selection on CNV calling performance of three chosen state-of-the-art tools: CODEX, CNVkit and exomeCopy. Two naive solutions (all samples as reference set and random selection) as well as two clustering methods (k-means and k nearest neighbours (kNN) with a variable number of clusters or group sizes) have been evaluated to discover the best performing sample selection method. RESULTS AND CONCLUSIONS: The performed experiments have shown that the appropriate selection of the reference sample set may greatly improve the CNV detection rate. In particular, we found that smart reduction of reference sample size may significantly increase the algorithms' precision while having negligible negative effect on sensitivity. We observed that a complete CNV calling process with the k-means algorithm as the selection method has significantly better time complexity than kNN-based solution.

SeQuiLa: an elastic, fast and scalable SQL-oriented solution for processing and querying genomic intervals.

SUMMARY: Efficient processing of large-scale genomic datasets has recently become possible due to the application of 'big data' technologies in bioinformatics pipelines. We present SeQuiLa-a distributed, ANSI SQL-compliant solution for speedy querying and processing of genomic intervals that is available as an Apache Spark package. Proposed range join strategy is significantly (∼22×) faster than the default Apache Spark implementation and outperforms other state-of-the-art tools for genomic intervals processing. AVAILABILITY AND IMPLEMENTATION: The project is available at http://biodatageeks.org/sequila/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Significance of diet in treated and untreated acne vulgaris.

The relationship between diet and acne is highly controversial. Several studies during the last decade have led dermatologists to reflect on a potential link between diet and acne. This article presents the latest findings on a potential impact that diet can have on pathogenesis of acne vulgaris. The association between diet and acne can no longer be dismissed. Compelling evidence shows that high glycemic load diets may exacerbate acne. Dairy ingestion appears to be weakly associated with acne and the roles of omega-3 fatty acids, dietary fiber, antioxidants, vitamin A, zinc and iodine remain to be elucidated. The question of what the impact of diet is on the course of acne vulgaris still remains unclear.