ABSTRACT
Septic arthritis, also known as infectious arthritis, is inflammation of the joints due to a wide range of pathogens, such as bacterial, fungal, mycobacterial, viral, or/and other pathogens; however, some opportunistic pathogens tend to affect immunocompromised patients and rarely infect immunocompetent patients. For example, Sphingomonas paucimobilis is an opportunistic pathogen with a particular tropism toward bones and soft tissues that rarely causes infections in immunocompetent humans. We present a case of Sphingomonas paucimobilis causing septic arthritis in a 34-year-old man who is medically free and with no history of previous surgeries or any other comorbidities. He was treated successfully by both pharmacological treatment and surgical intervention. To our knowledge, there are only four cases published in the literature involving Sphingomonas paucimobilis as a causative organism of septic arthritis affecting immunocompetent patients.
ABSTRACT
BACKGROUND: Traumatic brain injury is a leading cause of morbidity and mortality worldwide. The relationship between hyperoxia and outcomes in patients with TBI remains controversial. We assessed the effect of persistent hyperoxia on the neurological outcomes and survival of critically ill patients with moderate-severe TBI. METHOD: This was a retrospective cohort study of all adults with moderate-severe TBI admitted to the ICU between 1st January 2016 and 31st December 2019 and who required invasive mechanical ventilation. Arterial blood gas data was recorded within the first 3 hours of intubation and then after 6-12 hours and 24-48 hours. The patients were divided into two categories: Group I had a PaO2 < 120mmHg on at least two ABGs undertaken in the first twelve hours post intubation and Group II had a PaO2 ≥ 120mmHg on at least two ABGs in the same period. Multivariable logistic regression was performed to assess predictors of hospital mortality and good neurologic outcome (Glasgow outcome score ≥ 4). RESULTS: The study included 309 patients: 54.7% (n=169) in Group I and 45.3% (n=140) in Group II. Hyperoxia was not associated with increased mortality in the ICU (20.1% vs. 17.9%, p=0.62) or hospital (20.7% vs. 17.9%, p=0.53), moreover, the hospital discharge mean (SD) Glasgow Coma Scale (11.0(5.1) vs. 11.2(4.9), p=0.70) and mean (SD) Glasgow Outcome Score (3.1(1.3) vs. 3.1(1.2), p=0.47) were similar. In multivariable logistic regression analysis, persistent hyperoxia was not associated with increased mortality (adjusted odds ratio [aOR] 0.71, 95% CI 0.34-1.35, p=0.29). PaO2 within the first 3 hours was also not associated with mortality: 121-200mmHg: aOR 0.58, 95% CI 0.23-1.49, p=0.26; 201-300mmHg: aOR 0.66, 95% CI 0.27-1.59, p=0.35; 301-400mmHg: aOR 0.85, 95% CI 0.31-2.35, p=0.75 and >400mmHg: aOR 0.51, 95% CI 0.18-1.44, p=0.20; reference: PaO2 60-120mmHg within 3 hours. However, hyperoxia >400mmHg was associated with being less likely to have good neurological (GOS ≥4) outcome on hospital discharge (aOR 0.36, 95% CI 0.13-0.98, p=0.046; reference: PaO2 60-120mmHg within 3 hours. CONCLUSION: In intubated patients with moderate-severe TBI, hyperoxia in the first 48 hours was not independently associated with hospital mortality. However, PaO2 >400mmHg may be associated with a worse neurological outcome on hospital discharge.
ABSTRACT
RNA editing is a post-transcriptional or cotranscriptional process that changes the sequence of the precursor transcript by substitutions, insertions, or deletions. Almost all of the land plants undergo RNA editing in organelles (plastids and mitochondria). Although several software tools have been developed to identify RNA editing events, there has been a great challenge to distinguish true RNA editing events from genome variation, sequencing errors, and other factors. Here we introduce REDO, a comprehensive application tool for identifying RNA editing events in plant organelles based on variant call format files from RNA-sequencing data. REDO is a suite of Perl scripts that illustrate a bunch of attributes of RNA editing events in figures and tables. REDO can also detect RNA editing events in multiple samples simultaneously and identify the significant differential proportion of RNA editing loci. Comparing with similar tools, such as REDItools, REDO runs faster with higher accuracy, and more specificity at the cost of slightly lower sensitivity. Moreover, REDO annotates each RNA editing site in RNAs, whereas REDItools reports only possible RNA editing sites in genome, which need additional steps to obtain RNA editing profiles for RNAs. Overall, REDO can identify potential RNA editing sites easily and provide several functions such as detailed annotations, statistics, figures, and significantly differential proportion of RNA editing sites among different samples.
