Meta-colored Compacted de Bruijn Graphs

The colored compacted de Bruijn graph (c-dBG) has become a fundamental tool used across several areas of genomics and pangenomics. For example, it has been widely adopted by methods that perform read mapping or alignment, abundance estimation, and subsequent downstream analyses. These applications essentially regard the c-dBG as a map from k-mers to the set of references in which they appear. The c-dBG data structure should retrieve this set—the color of the k-mer—efficiently for any given k-mer, while using little memory. To aid retrieval, the colors are stored explicitly in the data structure and take considerable space for large reference collections, even when compressed. Reducing the space of the colors is therefore of utmost importance for large-scale sequence indexing. We describe the meta-colored compacted de Bruijn graph (Mac-dBG)—a new colored de Bruijn graph data structure where colors are represented holistically, i.e., taking into account their redundancy across the whole collection being indexed, rather than individually as atomic integer lists. This allows the factorization and compression of common sub-patterns across colors. While optimizing the space of our data structure is NP-hard, we propose a simple heuristic algorithm that yields practically good solutions. Results show that the Mac-dBG data structure improves substantially over the best previous space/time trade-off, by providing remarkably better compression effectiveness for the same (or better) query efficiency . This improved space/time trade-off is robust across different datasets and query workloads. Code availability. A C++17 implementation of the Mac-dBG is publicly available on GitHub at: https://github.com/jermp/fulgor

Spectrum Preserving Tilings Enable Sparse and Modular Reference Indexing

The reference indexing problem for k-mers is to pre-process a collection of reference genomic sequences so that the position of all occurrences of any queried k-mer can be rapidly identified. An efficient and scalable solution to this problem is fundamental for many tasks in bioinformatics. In this work, we introduce the spectrum preserving tiling (SPT), a general representation of that specifies how a set of tiles repeatedly occur to spell out the constituent reference sequences in. By encoding the order and positions where tiles occur, SPTs enable the implementation and analysis of a general class of modular indexes. An index over an SPT decomposes the reference indexing problem for k-mers into: (1) a k-mer-to-tile mapping; and (2) a tile-to-occurrence mapping. Recently introduced work to construct and compactly index k-mer sets can be used to efficiently implement the k-mer-to-tile mapping. However, implementing the tile-to-occurrence mapping remains prohibitively costly in terms of space. As reference collections become large, the space requirements of the tile-to-occurrence mapping dominates that of the k-mer-to-tile mapping since the former depends on the amount of total sequence while the latter depends on the number of unique k-mers in. To address this, we introduce a class of sampling schemes for SPTs that trade off speed to reduce the size of the tile-to-reference mapping. We implement a practical index with these sampling schemes in the tool pufferfish2. When indexing over 30,000 bacterial genomes, pufferfish2 reduces the size of the tile-to-occurrence mapping from 86.3 GB to 34.6 GB while incurring only a 3.6 slowdown when querying k-mers from a sequenced readset. Availability: pufferfish2 is implemented in Rust and available at https://github.com/COMBINE-lab/pufferfish2

FLOATING MULTIPLE UNIT MINITABLETS OF METOPROLOL SUCCINATE: FORMULATION, IN VITRO AND IN VIVO CHARACTERIZATION

Objective: In this present research, formulation of floating multiple unit minitablets of metoprolol succinate without using gas generating agent was attempted with an objective of increased residence time, sustained release, and improved oral bioavailability. Methods: Solid dispersions were prepared with lipophilic carriers such as compritol ATO888, Gelucire 43/01, Gelucire 39/01, and precirol ATO 05 was formulated using fusion technique. Neusillin US2 was used as an adsorbent. The solid dispersions were compressed into minitablets, weighing 20 mg, and then filled into ‘0’ size capsule. Results: Formulation F9, F10, F14, and F15 showed instantaneous floating lag time, i.e., 0 min, floating time more than 12 h, and sustained release up to 12 h. Pharmacokinetic study of the optimized formulation (F9) showed 2.46 times increase in area under the curve with increased residence time. Conclusion: Hence gelucire 43/01 based floating multiple unit minitablets of metoprolol succinate can be considered a promising approach

Early and Accurate Prediction of Heart Disease Using Machine Learning Model

Heart disease is one of the critical health issues and many people across the world are suffering with this disease. It is important to identify this disease in early stages to save many lives. The purpose of this article is to design a model to predict the heart diseases using machine learning techniques. This model is developed using classification algorithms, as they play important role in prediction. The model is developed using different classification algorithms which include Logistic Regression, Random Forest, Support vector machine, Gaussian Naïve Bayes, Gradient boosting, K-nearest neighbours, Multinomial Naïve bayes and Decision trees. Cleveland data repository is used to train and test the classifiers. In addition to this, feature selection algorithm named chi square is used to select key features from the input data set, which will decrease the execution time and increases the performance of the classifiers. Out of all the classifiers evaluated using performance metrics, Random forest is giving good accuracy. So, the model built using Random forest is efficient and feasible solution in identifying heart diseases and it can be implemented in healthcare which plays key role in the stream of cardiology. &nbsp

Stability indicating RP-HPLC method for the estimation of flucloxacillin sodium in a tablet dosage form

A Simple, accurate and precise method was developed and validated for the determination of flucloxacillin sodium in its tablet dosage form. The separation was eluted on xterra c18 column (4.6x150mm, 5micron) using a mixture of octane buffer and methanol as mobile phase in a ratio of (30:70) which was pumped through column at a flow rate of  1ml/min. Optimised wavelength for flucloxacillin was 237nm, the retention time was 2.305minutes and the percentage purity was found to be 98.14%. System suitability parameters such as theoretical plate and tailing factor for flucloxacillin sodium was found to be 2991.64 and 1.90 respectively, the proposed method was validated as per ICH guidelines (ICH, Q2 AND (R1)) the method was found to be linear at the concentration range of 20-100µg/ml and the correlation coefficient (r2) value was found to be 0.9994 percentage RSD for precision was 0.9% and percentage RSD for ruggedness was 0.5%. The precision study was precise, robust and repeatable. The LOD and LOQ values are 2.98 and 9.98 respectively. Hence the suggested RP-HPLC method can be used for routine analysis for flucloxacillin sodium in tablet dosage form

Structural insights into the mechanism of archaellar rotational switching

Signal transduction via phosphorylated CheY towards the flagellum and the archaellum involves a conserved mechanism of CheY phosphorylation and subsequent conformational changes within CheY. This mechanism is conserved among bacteria and archaea, despite substantial differences in the composition and architecture of archaellum and flagellum, respectively. Phosphorylated CheY has higher affinity towards the bacterial C-ring and its binding leads to conformational changes in the flagellar motor and subsequent rotational switching of the flagellum. In archaea, the adaptor protein CheF resides at the cytoplasmic face of the archaeal C-ring formed by the proteins ArlCDE and interacts with phosphorylated CheY. While the mechanism of CheY binding to the C-ring is well-studied in bacteria, the role of CheF in archaea remains enigmatic and mechanistic insights are absent. Here, we have determined the atomic structures of CheF alone and in complex with activated CheY by X-ray crystallography. CheF forms an elongated dimer with a twisted architecture. We show that CheY binds to the C-terminal tail domain of CheF leading to slight conformational changes within CheF. Our structural, biochemical and genetic analyses reveal the mechanistic basis for CheY binding to CheF and allow us to propose a model for rotational switching of the archaellum. Signal transduction via phosphorylated CheY is conserved in bacteria and archaea. In this study, the authors employ structural biochemistry combined with cell biology to delineate the mechanism of CheY recognition by the adaptor protein CheF

Identification of intracellular bacteria from multiple single-cell RNA-seq platforms using CSI-Microbes

The study of the tumor microbiome has been garnering increased attention. We developed a computational pipeline (CSI-Microbes) for identifying microbial reads from single-cell RNA sequencing (scRNA-seq) data and for analyzing differential abundance of taxa. Using a series of controlled experiments and analyses, we performed the first systematic evaluation of the efficacy of recovering microbial unique molecular identifiers by multiple scRNA-seq technologies, which identified the newer 10x chemistries (3' v3 and 5') as the best suited approach. We analyzed patient esophageal and colorectal carcinomas and found that reads from distinct genera tend to co-occur in the same host cells, testifying to possible intracellular polymicrobial interactions. Microbial reads are disproportionately abundant within myeloid cells that up-regulate proinflammatory cytokines like IL1Β and CXCL8, while infected tumor cells up-regulate antigen processing and presentation pathways. These results show that myeloid cells with bacteria engulfed are a major source of bacterial RNA within the tumor microenvironment (TME) and may inflame the TME and influence immunotherapy response

Zinc for the treatment of diarrhoea: effect on diarrhoea morbidity, mortality and incidence of future episodes

Background Zinc supplementation for the treatment of diarrhoea has been shown to decrease the duration and severity of the diarrhoeal episode, diarrhoea hospitalization rates and, in some studies, all-cause mortality. Using multiple outcome measures, we sought to estimate the effect of zinc for the treatment of diarrhoea on diarrhoea mortality and subsequent pneumonia mortality

A practical method for optimum seismic design of friction wall dampers

Friction control systems have been widely used as one of the efficient and cost effective solutions to control structural damage during strong earthquakes. However, the height-wise distribution of slip loads can significantly affect the seismic performance of the strengthened frames. In this study, a practical design methodology is developed for more efficient design of friction wall dampers by performing extensive nonlinear dynamic analyses on 3, 5, 10, 15, and 20-story RC frames subjected to seven spectrum-compatible design earthquakes and five different slip load distribution patterns. The results show that a uniform cumulative distribution can provide considerably higher energy dissipation capacity than the commonly used uniform slip load pattern. It is also proved that for a set of design earthquakes, there is an optimum range for slip loads that is a function of number of stories. Based on the results of this study, an empirical equation is proposed to calculate a more efficient slip load distribution of friction wall dampers for practical applications. The efficiency of the proposed method is demonstrated through several design examples

Relative Abundance of Transcripts (RATs):Identifying differential isoform abundance from RNA-seq [version 1; referees: 1 approved, 2 approved with reservations]

The biological importance of changes in RNA expression is reflected by the wide variety of tools available to characterise these changes from RNA-seq data. Several tools exist for detecting differential transcript isoform usage (DTU) from aligned or assembled RNA-seq data, but few exist for DTU detection from alignment-free RNA-seq quantifications. We present the RATs, an R package that identifies DTU transcriptome-wide directly from transcript abundance estimates. RATs is unique in applying bootstrapping to estimate the reliability of detected DTU events and shows good performance at all replication levels (median false positive fraction < 0.05). We compare RATs to two existing DTU tools, DRIM-Seq & SUPPA2, using two publicly available simulated RNA-seq datasets and a published human RNA-seq dataset, in which 248 genes have been previously identified as displaying significant DTU. RATs with default threshold values on the simulated Human data has a sensitivity of 0.55, a Matthews correlation coefficient of 0.71 and a false discovery rate (FDR) of 0.04, outperforming both other tools. Applying the same thresholds for SUPPA2 results in a higher sensitivity (0.61) but poorer FDR performance (0.33). RATs and DRIM-seq use different methods for measuring DTU effect-sizes complicating the comparison of results between these tools, however, for a likelihood-ratio threshold of 30, DRIM-Seq has similar FDR performance to RATs (0.06), but worse sensitivity (0.47). These differences persist for the simulated drosophila dataset. On the published human RNA-seq dataset the greatest agreement between the tools tested is 53%, observed between RATs and SUPPA2. The bootstrapping quality filter in RATs is responsible for removing the majority of DTU events called by SUPPA2 that are not reported by RATs. All methods, including the previously published qRT-PCR of three of the 248 detected DTU events, were found to be sensitive to annotation differences between Ensembl v60 and v87