Impact of Inhaled Nitric Oxide (iNO) on the Outcome of COVID-19 Associated ARDS.

Inhaled nitric oxide (iNO) can improve oxygenation in acute respiratory syndrome (ARDS), has anti-inflammatory and antithrombotic effects, and can inhibit coronavirus- replication. The study aim was to investigate the impact of iNO in COVID-19 associated ARDS (CARDS) on oxygenation, the length of mechanical ventilation (MV), the level of inflammatory markers and the rate of thrombotic events during ICU stay. This was a retrospective, observational, monocentric study analyzing the effect of INO (15 parts per million) vs.

Alternative techniques for cardiopulmonary resuscitation in extreme environments - A scoping review.

Background: Cardiopulmonary resuscitation (CPR) is essential for saving lives during cardiac arrest, but performing CPR in extreme environments poses unique challenges. In scenarios ranging from hypogravity or microgravity to confined spaces like aeroplanes and underwater scenarios, traditional CPR techniques may be inadequate. This scoping review aims to identify alternative chest compression techniques, synthesise current knowledge, and pinpoint research gaps in resuscitation for cardiac arrest in extreme conditions.

Weaning failure due to isolated residual diaphragmatic paralysis after cervical spinal cord ischemia following aortic surgery- a case report.

Background: Bilateral diaphragmatic dysfunction can lead to dyspnea and recurrent respiratory failure. In rare cases, it may result from high cervical spinal cord ischemia (SCI) due to anterior spinal artery syndrome (ASAS). We present a case of a patient experiencing persistent isolated diaphragmatic paralysis after SCI at level C3/C4 following thoracic endovascular aortic repair (TEVAR) for Kommerell's diverticulum.

Comparative Genomic Analysis of Bacterial Data in BV-BRC: An Example Exploring Antimicrobial Resistance.

As genomic and related data continue to expand, research biologists are often hampered by the computational hurdles required to analyze their data. The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Centers (BRC) to assist researchers with their analysis of genome sequence and other omics-related data. Recently, the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD), and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs merged to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) at https://www.

The Value of Next-Generation Sequencing in Diagnosis and Therapy of Critically Ill Patients with Suspected Bloodstream Infections: A Retrospective Cohort Study.

Bloodstream infection (BSI), a frequent cause of severe sepsis, is a life-threatening complication in critically ill patients and still associated with a high mortality rate. Rapid pathogen identification from blood is crucial for an early diagnosis and the treatment of patients with suspected BSI. For this purpose, novel diagnostic tools on the base of genetic analysis have emerged for clinical application.

Effectiveness of CPR in Hypogravity Conditions-A Systematic Review.

(1) Background: Cardiopulmonary resuscitation (CPR), as a form of basic life support, is critical for maintaining cardiac and cerebral perfusion during cardiac arrest, a medical condition with high expected mortality. Current guidelines emphasize the importance of rapid recognition and prompt initiation of high-quality CPR, including appropriate cardiac compression depth and rate. As space agencies plan missions to the Moon or even to explore Mars, the duration of missions will increase and with it the chance of life-threatening conditions requiring CPR.

Supervised extraction of near-complete genomes from metagenomic samples: A new service in PATRIC.

Large amounts of metagenomically-derived data are submitted to PATRIC for analysis. In the future, we expect even more jobs submitted to PATRIC will use metagenomic data. One in-demand use case is the extraction of near-complete draft genomes from assembled contigs of metagenomic origin.

The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities.

The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org).

A machine learning-based service for estimating quality of genomes using PATRIC.

Background: Recent advances in high-volume sequencing technology and mining of genomes from metagenomic samples call for rapid and reliable genome quality evaluation. The current release of the PATRIC database contains over 220,000 genomes, and current metagenomic technology supports assemblies of many draft-quality genomes from a single sample, most of which will be novel.

Description: We have added two quality assessment tools to the PATRIC annotation pipeline.

Assembly, Annotation, and Comparative Genomics in PATRIC, the All Bacterial Bioinformatics Resource Center.

In the "big data" era, research biologists are faced with analyzing new types that usually require some level of computational expertise. A number of programs and pipelines exist, but acquiring the expertise to run them, and then understanding the output can be a challenge.The Pathosystems Resource Integration Center (PATRIC, www.

Phage Genome Annotation Using the RAST Pipeline.

Phages are complex biomolecular machineries that have to survive in a bacterial world. Phage genomes show many adaptations to their lifestyle such as shorter genes, reduced capacity for redundant DNA sequences, and the inclusion of tRNAs in their genomes. In addition, phages are not free-living, they require a host for replication and survival.

PATRIC as a unique resource for studying antimicrobial resistance.

The Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org) is designed to provide researchers with the tools and services that they need to perform genomic and other 'omic' data analyses.

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation.

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems.

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center.

The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center (https://www.patricbrc.org).

Modeling central metabolism and energy biosynthesis across microbial life.

Background: Automatically generated bacterial metabolic models, and even some curated models, lack accuracy in predicting energy yields due to poor representation of key pathways in energy biosynthesis and the electron transport chain (ETC). Further compounding the problem, complex interlinking pathways in genome-scale metabolic models, and the need for extensive gapfilling to support complex biomass reactions, often results in predicting unrealistic yields or unrealistic physiological flux profiles.

Results: To overcome this challenge, we developed methods and tools ( http://coremodels.

From DNA to FBA: How to Build Your Own Genome-Scale Metabolic Model.

Microbiological studies are increasingly relying on in silico methods to perform exploration and rapid analysis of genomic data, and functional genomics studies are supplemented by the new perspectives that genome-scale metabolic models offer. A mathematical model consisting of a microbe's entire metabolic map can be rapidly determined from whole-genome sequencing and annotating the genomic material encoded in its DNA. Flux-balance analysis (FBA), a linear programming technique that uses metabolic models to predict the phenotypic responses imposed by environmental elements and factors, is the leading method to simulate and manipulate cellular growth in silico.

Antimicrobial Resistance Prediction in PATRIC and RAST.

The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decision-making and improve reaction time. At PATRIC (http://patricbrc.

A relationship between temperature and aggression in NFL football penalties.

Background: Increased ambient temperature has been implicated in increased physical aggression, which has important practical consequences. The present study investigates this established relationship between aggressive behavior and ambient temperature in the highly aggressive context of professional football in the National Football League (NFL).

Methods: Using a publicly available dataset, authors conducted multiple hierarchical regression analyses on game-level data (2326 games).

Reconstruction of the Regulatory Network for Bacillus subtilis and Reconciliation with Gene Expression Data.

We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of Bacillus subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs, and regulated operons.

RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes.

The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e.

Enabling comparative modeling of closely related genomes: example genus Brucella.

For many scientific applications, it is highly desirable to be able to compare metabolic models of closely related genomes. In this short report, we attempt to raise awareness to the fact that taking annotated genomes from public repositories and using them for metabolic model reconstructions is far from being trivial due to annotation inconsistencies. We are proposing a protocol for comparative analysis of metabolic models on closely related genomes, using fifteen strains of genus Brucella, which contains pathogens of both humans and livestock.

High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource.

The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes.

In search of genome annotation consistency: solid gene clusters and how to use them.

Maintaining consistency in genome annotations is important for supporting many computational tasks, particularly metabolic modeling. The SEED project has implemented a process that improves annotation consistencies across microbial genomes for proteins with conserved sequences and genomic context. In this research report, we describe this process and show how this effort has resulted in improvements to microbial genome annotations in the SEED.

The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST).

In 2004, the SEED (http://pubseed.theseed.org/) was created to provide consistent and accurate genome annotations across thousands of genomes and as a platform for discovering and developing de novo annotations.