Small RNA interactome of pathogenic E. coli revealed through crosslinking of RNase E.

RNA sequencing studies have identified hundreds of non-coding RNAs in bacteria, including regulatory small RNA (sRNA). However, our understanding of sRNA function has lagged behind their identification due to a lack of tools for the high-throughput analysis of RNA-RNA interactions in bacteria. Here we demonstrate that in vivo sRNA-mRNA duplexes can be recovered using UV-crosslinking, ligation and sequencing of hybrids (CLASH). Many sRNAs recruit the endoribonuclease, RNase E, to facilitate processing of mRNAs. We were able to recover base-paired sRNA-mRNA duplexes in association with RNase E, allowing proximity-dependent ligation and sequencing of cognate sRNA-mRNA pairs as chimeric reads. We verified that this approach captures bona fide sRNA-mRNA interactions. Clustering analyses identified novel sRNA seed regions and sets of potentially co-regulated target mRNAs. We identified multiple mRNA targets for the pathotype-specific sRNA Esr41, which was shown to regulate colicin sensitivity and iron transport in E. coli Numerous sRNA interactions were also identified with non-coding RNAs, including sRNAs and tRNAs, demonstrating the high complexity of the sRNA interactome.

How to interpret polysomnography.

A 5-year-old child presents to a paediatric clinic with their parents because of concerns about snoring, which is loud, every night and associated with respiratory pauses. This has been present for 6 months. Can clinical evaluation diagnose sleep-disordered breathing in children or are further investigations required? Should further investigations include oximetry or polysomnography? If a polysomnogram is performed, how are the results interpreted? In this paper we describe the indications for polysomnography, outline the parameters measured and decode a clinical polysomnography report.

Frail patients having vascular surgery during the early COVID-19 pandemic experienced high rates of adverse perioperative events and amputation.

BACKGROUND: Frailty predicts adverse perioperative outcomes and increased mortality in patients having vascular surgery. Frailty assessment is a potential tool to inform resource allocation, and shared decision-making about vascular surgery in the resource constrained COVID-19 pandemic environment. This cohort study describes the prevalence of frailty in patients having vascular surgery and the association between frailty, mortality and perioperative outcomes. METHODS: The COVID-19 Vascular Service in Australia (COVER-AU) prospective cohort study evaluates 30-day and six-month outcomes for consecutive patients having vascular surgery in 11 Australian vascular units, March-July 2020. The primary outcome was mortality, with secondary outcomes procedure-related outcomes and hospital utilization. Frailty was assessed using the nine-point visual Clinical Frailty Score, scores of 5 or more considered frail. RESULTS: Of the 917 patients enrolled, 203 were frail (22.1%). The 30 day and 6 month mortality was 2.0% (n = 20) and 5.9% (n = 35) respectively with no significant difference between frail and non-frail patients (OR 1.68, 95%CI 0.79-3.54). However, frail patients stayed longer in hospital, had more perioperative complications, and were more likely to be readmitted or have a reoperation when compared to non-frail patients. At 6 months, frail patients had twice the odds of major amputation compared to non-frail patients, after adjustment (OR 2.01; 95% CI 1.17-3.78), driven by a high rate of amputation during the period of reduced surgical activity. CONCLUSION: Our findings highlight that older, frail patients, experience potentially preventable adverse outcomes and there is a need for targeted interventions to optimize care, especially in times of healthcare stress.

Acute kidney injury secondary to severe delayed haemolysis in intravenous artesunate use for severe malaria.

The use of artemisinin derivatives has been recommended by the WHO guidelines in malaria treatment largely due to its rapid parasite clearance and safety profile. This case report details the development of delayed haemolysis and subsequent severe acute kidney injury (AKI) 13 days after commencing intravenous artesunate treatment for malaria in an Australian returned traveller. Delayed haemolysis may be an under-recognised complication following artesunate use and if severe, can be complicated by AKI. Therefore, close patient follow-up following treatment is required to ensure prompt recognition of this phenomenon.

Potassium levels after liver reperfusion in adult patients undergoing cadaveric liver transplantation: A retrospective cohort study.

BACKGROUND: Hyperkalemia is a common cause of arrhythmias in patients undergoing liver transplantation. We examined the pattern of change of potassium levels during and immediately after reperfusion of the donor liver. MATERIALS AND METHODS: Potassium levels of 30 consecutive adult patients undergoing cadaveric liver transplantation were assessed before and after liver reperfusion. Changes in potassium levels over 13 predefined timepoints were analyzed. Primary aim: to describe the pattern of change of potassium levels during the reperfusion period. Correlation between changes in potassium levels during reperfusion and a-priori variables were investigated. RESULTS: Baseline median (IQR) potassium levels were 4.1 (3.8:4.5) mmol/L. Thirteen patients (43%) developed hyperkalemia, 10 (33%) of whom developed severe hyperkalemia. Potassium levels peaked at 80 s post reperfusion, plateaued until 2 min, before returning toward baseline values at 5 min. There was a strong association between pre-reperfusion/baseline potassium levels and peak potassium values during reperfusion (95%CI: 0.26 to 0.77, p < 0.001). A baseline potassium level of 4.45 mmol/L was a good predictor of reperfusion hyperkalemia with a sensitivity of 69.2% and specificity of 94.1% (AUC = 0.894, 95%CI: 0.779 to 1.000, p < 0.001). CONCLUSION: Hyperkalemia during cadaveric liver transplantation is common affecting almost 1 in 2 patients during reperfusion. During reperfusion potassium levels peaked within 2 min and over a third of patients developed severe hyperkalemia. Higher peak potassium levels correlated strongly with higher pre-reperfusion potassium values. These findings guide clinicians with timing of sampling of blood to check for hyperkalemia and identify modifiable factors associated with the development of hyperkalemia.