Strategies for prediction of drug-resistant pathogens and empiric antibiotic selection in community-acquired pneumonia.

PURPOSE OF REVIEW: Although most patients with community-acquired pneumonia (CAP) are appropriately treated with narrow-spectrum antibiotics, predicting which patients require coverage of drug-resistant pathogens (DRP) remains a challenge. The 2019 American Thoracic Society/Infectious Diseases Society of America CAP guidelines endorse using locally validated prediction models for DRP. Here we review risk factors for DRP and provide a summary of available risk prediction models. RECENT FINDINGS: Both inadequate initial empiric spectrum as well as unnecessary broad-spectrum antibiotic use are associated with poor outcomes in CAP. Multiple prediction models for DRP-based patient-level risk factors have been published, with some variation in included predictor variables and test performance characteristics. Seven models have been robustly externally validated, and implementation data have been published for two of these models. All models demonstrated better performance than the healthcare-associated pneumonia criteria, with most favoring sensitivity over specificity. We also report validation of the novel, risk factor-based treatment algorithm proposed in the American Thoracic Society/Infectious Diseases Society of America guidelines which strongly favors specificity over sensitivity, especially in nonsevere pneumonia. SUMMARY: Using patient-level risk factors to guide the decision whether to prescribe broad-spectrum antibiotics is a rational approach to treatment. Several viable candidate prediction models are available. Hospitals should evaluate the local performance of existing scores before implementing in routine clinical practice.

Increased urinary osmolyte excretion indicates chronic kidney disease severity and progression rate.

Background: Chronic kidney disease (CKD) is a recognized global health problem. While some CKD patients remain stable after initial diagnosis, others can rapidly progress towards end-stage renal disease (ESRD). This makes biomarkers capable of detecting progressive forms of CKD extremely valuable, especially in non-invasive biofluids such as urine. Screening for metabolite markers using non-targeted metabolomic techniques like nuclear magnetic resonance spectroscopy is increasingly applied to CKD research. Methods: A cohort of CKD patients (n = 227) with estimated glomerular filtration rates (eGFRs) ranging from 9.4-130 mL/min/1.73 m2 was evaluated and urine metabolite profiles were characterized in relation to declining eGFR. Nested in this cohort, a retrospective subset (n = 57) was investigated for prognostic metabolite markers of CKD progression, independent of baseline eGFR. A transcriptomic analysis of murine models of renal failure was performed to validate selected metabolomic findings. Results: General linear modeling revealed 11 urinary metabolites with significant associations to reduced eGFR. Linear modelling specifically showed that increased urine concentrations of betaine (P < 0.05) and myo-inositol (P < 0.05) are significant prognostic markers of CKD progression. Conclusions: Renal organic osmolytes, betaine and myo-inositol play a critical role in protecting renal cells from hyperosmotic stress. Kidney tissue transcriptomics of murine preclinical experimentation identified decreased expression of Slc6a12 and Slc5a11 mRNA in renal tissue consistent with defective tubular transport of these osmolytes. Imbalances in renal osmolyte regulation lead to increased renal cell damage and thus more progressive forms of CKD. Increases in renal osmolytes in urine could provide clinical diagnostic and prognostic information on CKD outcomes.

(1)H NMR-based metabolite profiling workflow to reduce inter-sample chemical shift variations in urine samples for improved biomarker discovery.

Metabolite profiling of urine has seen much advancement in recent years, and its analysis by nuclear magnetic resonance (NMR) spectroscopy has become well established. However, the highly variable nature of human urine still requires improved protocols despite some standardization. In particular, diseases such as kidney disease can have a profound effect on the composition of urine and generate a highly diverse sample set for clinical studies. Large variations in pH and the cationic concentration of urine play an important role in creating positional noise within datasets generated from NMR. We demonstrate positional noise to be a confounding variable for multivariate statistical tools such as statistical total correlation spectroscopy (STOCSY), thereby hindering the process of biomarker discovery. We present a two-dimensional buffering system using potassium fluoride (KF) and phosphate buffer to reduce positional noise in metabolomic data generated from urine samples with various levels of proteinuria. KF reduces positional noise in citrate peaks, by decreasing the mean relative standard deviation (RSD) from 0.17 to 0.09. By reducing positional noise with KF, STOCSY analysis of citrate peaks saw significant improvement. We further aligned spectral data using a recursive segment-wise peak alignment (RSPA) method, which leads to further improvement of the positional noise (RSD = 0.06). These results were validated using diverse selection of metabolites which lead to an overall improvement in positional noise using the suggested protocol. In summary, we provide an improved workflow for urine metabolite biomarker discovery to achieve higher data quality for better pathophysiological understanding of human diseases. Graphical abstract Citrate peaks in the range 2.75-2.5 ppm from datasets with different sample preparation protocols and with/without in silico alignment. A Citrate peaks with standard phosphate buffering and without in silico alignment. B citrate peaks with standard phosphate buffering and with in silico alignment. C citrate peak with additional potassium fluoride and standard phosphate buffering without in silico alignment. D citrate peaks with additional potassium fluoride and standard phosphate buffering with in silico alignment. Below the respective spectrum are displayed the percent relative standard deviation (RSD) of the respective citrate peaks. This is a measure of the positional noise of peaks within a (1)H NMR analysis. It can be seen that D performs the best in reducing positional noise of citrate peaks. E-H STOCSY analysis of correlating spectral features with the driver peak at 2.675 ppm (see red arrow) to identify structural correlations. As a, b, c, and d are known to be structurally correlated, STOCSY analysis should reveal r (2) = 1 if data is perfectly aligned and can therefore be used as a measure of peak alignment. E Strong positional noise does not allow identifying the c and d peaks of the AB system to be correlated. F, G Neither in silico alignment or KF addition alone can completely improve the alignment and therefore increase the correlations. H Highly improved alignment by combining both KF addition and in silico alignment reduces positional noise and elucidates all four citrate peaks to be strongly correlated.

Whole-body vibration attenuates the increase in leg arterial stiffness and aortic systolic blood pressure during post-exercise muscle ischemia.

Exercise with whole-body vibration (WBV) decreases brachial-ankle pulse wave velocity (baPWV), a marker of systemic arterial stiffness. To examine the effect of WBV on arterial responses, 12 young men underwent three experimental trials: (1) no-exercise control (CON), (2) static squat with WBV, and (3) static squat without WBV (no-WBV). Bilateral baPWV and femoral-ankle PWV (faPWV), carotid-femoral PWV (cfPWV), augmentation index (AIx), first (P1) and second (P2) systolic peaks, aortic systolic blood pressure (aSBP), and heart rate (HR) were assessed at rest, during 4-min post-exercise muscle ischemia (PEMI) on the left thigh, and 4-min recovery. During PEMI, right faPWV increased (P < 0.05) after no-WBV and did not change after CON and WBV. Right baPWV, P2, and aSBP increased (P < 0.05) after both exercise trials, but the increase was lower (P < 0.05) after WBV than no-WBV. The increases in cfPWV (P < 0.05), AIx (P < 0.05), P1 (P < 0.01), and HR (P < 0.05) were similar in both trials during PEMI. During recovery, right faPWV and baPWV remained similar than rest after WBV and CON, but remained elevated (P < 0.05) after no-WBV. Aortic SBP, P1, and P2 remained elevated (P < 0.05) in both exercise trials during recovery, but the levels were lower (P < 0.05) than PEMI. Left faPWV and baPWV were reduced (P < 0.05) from rest in the three trials. CfPWV, AIx, and HR returned to resting levels in both exercises. WBV prevents the increases in faPWV and attenuates the increase in baPWV and aSBP induced by post-static squat muscle ischemia due to an attenuated P2 response.

Proteomics and Metabolomics for AKI Diagnosis.

Acute kidney injury (AKI) is a severe and frequent condition in hospitalized patients. Currently, no efficient therapy of AKI is available. Therefore, efforts focus on early prevention and potentially early initiation of renal replacement therapy to improve the outcome in AKI. The detection of AKI in hospitalized patients implies the need for early, accurate, robust, and easily accessible biomarkers of AKI evolution and outcome prediction because only a narrow window exists to implement the earlier-described measures. Even more challenging is the multifactorial origin of AKI and the fact that the changes of molecular expression induced by AKI are difficult to distinguish from those of the diseases associated or causing AKI as shock or sepsis. During the past decade, a considerable number of protein biomarkers for AKI have been described and we expect from recent advances in the field of omics technologies that this number will increase further in the future and be extended to other sorts of biomolecules, such as RNAs, lipids, and metabolites. However, most of these biomarkers are poorly defined by their AKI-associated molecular context. In this review, we describe the state-of-the-art tissue and biofluid proteomic and metabolomic technologies and new bioinformatics approaches for proteomic and metabolomic pathway and molecular interaction analysis. In the second part of the review, we focus on AKI-associated proteomic and metabolomic biomarkers and briefly outline their pathophysiological context in AKI.

Natural oxygenation of Champagne wine during ageing on lees: A metabolomics picture of hormesis.

The oxygenation of Champagne wine after 4 and 6 years of aging on lees in bottle was investigated by FTICR-MS and UPLC-Q-TOF-MS. Three levels of permeability were considered for the stoppers, ranging from 0.2 to 1.8 mg/L/year of oxygen transfer rate. Our results confirmed a good repeatability of ultra-high resolution FTICR-MS, both in terms of m/z and coefficient of variation of peak intensities among biological replicates. Vintages appeared to be the most discriminated features, and metabolite annotations suggested that the oldest wines (2006) were characterized by a higher sensitivity towards oxygenation. Within each vintage, the oxygenation mechanisms appeared to be different for low and high ingresses of oxygen, in agreement with the hormesis character of wine oxygenation. In the particular case of single variety wines and for a given level of stopper permeability, our results also showed that variety discrimination could be easily achieved among wines.

Metabolic determinants of electrical failure in ex-vivo canine model of cardiac arrest: evidence for the protective role of inorganic pyrophosphate.

RATIONALE: Deterioration of ventricular fibrillation (VF) into asystole or severe bradycardia (electrical failure) heralds a fatal outcome of cardiac arrest. The role of metabolism in the timing of electrical failure remains unknown. OBJECTIVE: To determine metabolic factors of early electrical failure in an ex-vivo canine model of cardiac arrest (VF+global ischemia). METHODS AND RESULTS: Metabolomic screening was performed in left ventricular biopsies collected before and after 0.3, 2, 5, 10 and 20 min of VF and global ischemia. Electrical activity was monitored via plunge needle electrodes and pseudo-ECG. Four out of nine hearts exhibited electrical failure at 10.1±0.9 min (early-asys), while 5/9 hearts maintained VF for at least 19.7 min (late-asys). As compared to late-asys, early-asys hearts had more ADP, less phosphocreatine, and higher levels of lactate at some time points during VF/ischemia (all comparisons p<0.05). Pre-ischemic samples from late-asys hearts contained ∼25 times more inorganic pyrophosphate (PPi) than early-asys hearts. A mechanistic role of PPi in cardioprotection was then tested by monitoring mitochondrial membrane potential (ΔΨ) during 20 min of simulated-demand ischemia using potentiometric probe TMRM in rabbit adult ventricular myocytes incubated with PPi versus control group. Untreated myocytes experienced significant loss of ΔΨ while in the PPi-treated myocytes ΔΨ was relatively maintained throughout 20 min of simulated-demand ischemia as compared to control (p<0.05). CONCLUSIONS: High tissue level of PPi may prevent ΔΨm loss and electrical failure at the early phase of ischemic stress. The link between the two protective effects may involve decreased rates of mitochondrial ATP hydrolysis and lactate accumulation.

Whole-body vibration training reduces arterial stiffness, blood pressure and sympathovagal balance in young overweight/obese women.

Obesity is associated with early cardiovascular dysfunction and reduced muscle strength. Whole-body vibration (WBV) training may improve arterial function and muscle strength. The effects of WBV training on arterial stiffness (brachial-ankle pulse wave velocity, baPWV), wave reflection (augmentation index, AIx), brachial systolic blood pressure (bSBP), aortic systolic blood pressure (aSBP), heart rate variability, and muscle strength (one-repetition maximum, 1RM) were examined in 10 young (21 ± 2 year) overweight/obese women (body mass index, BMI = 29.9 ± 0.8 kg m(-2)). Participants were randomized to a 6-week WBV training or non-exercising control (CON) period in a crossover design. WBV training (3 days × week) consisted of static and dynamic squats and calf raises with vibration intensity at 25-30 Hz and 1-2 mm amplitude (2.83-4.86 G). There were significant (P<0.05) decreases in baPWV (-0.9 ± 0.3 m s(-1)), AIx (-8.0 ± 2.2 %), bSBP (-5.3 ± 1.5 mm Hg), aSBP (-5.2 ± 2.1 mm Hg), low-frequency power (-0.13 ± 0.05 nu) and sympathovagal balance (LF/HF, -0.42 ± 0.16) after WBV training compared with CON. Significant (P<0.05) increases in high-frequency power (HF, 0.19 ± 0.04 nu) and leg extension 1RM (8.2 ± 2.3 kg) occurred after WBV training compared with CON. Six weeks of WBV training decreased systemic arterial stiffness and aSBP via improvements in wave reflection and sympathovagal balance in young overweight/obese normotensive women. WBV training may benefit arterial function and muscle strength in deconditioned individuals who cannot perform conventional exercise.