Reduction of trimethylamine N-oxide to trimethylamine by the human gut microbiota: supporting evidence for ‘metabolic retroversion’

Dietary sources of methylamines such as choline, trimethylamine (TMA), trimethylamine N-oxide (TMAO), phosphatidylcholine (PC) and carnitine are present in a number of foodstuffs, including meat, fish, nuts and eggs. It is recognized that the gut microbiota is able to convert choline to TMA in a fermentation-like process. Similarly, PC and carnitine are converted to TMA by the gut microbiota. It has been suggested that TMAO is subject to ‘metabolic retroversion’ in the gut (i.e. it is reduced to TMA by the gut microbiota, with this TMA being oxidized to produce TMAO in the liver). Sixty-six strains of human faecal and caecal bacteria were screened on solid and liquid media for their ability to utilize trimethylamine N-oxide (TMAO), with metabolites in spent media profiled by Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy. Enterobacteriaceae produced mostly TMA from TMAO, with caecal/small intestinal isolates of Escherichia coli producing more TMA than their faecal counterparts. Lactic acid bacteria (enterococci, streptococci, bifidobacteria) produced increased amounts of lactate when grown in the presence of TMAO, but did not produce large amounts of TMA from TMAO. The presence of TMAO in media increased the growth rate of Enterobacteriaceae; while it did not affect the growth rate of lactic acid bacteria, TMAO increased the biomass of these bacteria. The positive influence of TMAO on Enterobacteriaceae was confirmed in anaerobic, stirred, pH-controlled batch culture fermentation systems inoculated with human faeces, where this was the only bacterial population whose growth was significantly stimulated by the presence of TMAO in the medium. We hypothesize that dietary TMAO is used as an alternative electron acceptor by the gut microbiota in the small intestine/proximal colon, and contributes to microbial population dynamics upon its utilization and retroversion to TMA, prior to absorption and secondary conversion to TMAO by hepatic flavin-containing monooxygenases. Our findings support the idea that oral TMAO supplementation is a physiologically-stable microbiota-mediated strategy to deliver TMA at the gut barrier

Fast Locality-Sensitive Hashing Frameworks for Approximate Near Neighbor Search

The Indyk-Motwani Locality-Sensitive Hashing (LSH) framework (STOC 1998) is a general technique for constructing a data structure to answer approximate near neighbor queries by using a distribution $\mathcal{H}$ over locality-sensitive hash functions that partition space. For a collection of $n$ points, after preprocessing, the query time is dominated by $O(n^{\rho} \log n)$ evaluations of hash functions from $\mathcal{H}$ and $O(n^{\rho})$ hash table lookups and distance computations where $\rho \in (0,1)$ is determined by the locality-sensitivity properties of $\mathcal{H}$. It follows from a recent result by Dahlgaard et al. (FOCS 2017) that the number of locality-sensitive hash functions can be reduced to $O(\log^2 n)$, leaving the query time to be dominated by $O(n^{\rho})$ distance computations and $O(n^{\rho} \log n)$ additional word-RAM operations. We state this result as a general framework and provide a simpler analysis showing that the number of lookups and distance computations closely match the Indyk-Motwani framework, making it a viable replacement in practice. Using ideas from another locality-sensitive hashing framework by Andoni and Indyk (SODA 2006) we are able to reduce the number of additional word-RAM operations to $O(n^\rho)$.Comment: 15 pages, 3 figure

Prognostic Impact of Admission Blood Glucose for All-Cause Mortality in Patients with Acute Coronary Syndromes: Added Value on Top of GRACE Risk Score

BACKGROUND: Abnormal glucose metabolism is a predictor of worse outcome after acute coronary syndrome (ACS). However, this parameter is not included in risk prediction scores, including GRACE risk score. We sought to evaluate whether the inclusion of blood glucose at admission in a model with GRACE risk score improves risk stratification. METHODS: Study of consecutive patients included in a single centre registry of ACS. Our primary endpoint was the occurrence of all-cause mortality at one-year follow-up. The ability of the two logistic regression models (GRACE risk score alone and in combination with blood glucose) to predict death was analysed. Continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI), with corresponding 95% confidence intervals (CIs), were also calculated. RESULTS: We included 2099 patients, with a mean age of 64 (SD=13) years, 69% males. In our sample, 55.1% presented with ST-segment elevation ACS and 13.1% in Killip class ≥ 2. Only 25% were known diabetic at admission. In-hospital mortality was 5.8% and 9.7% at one-year follow-up. The best cut-point for blood glucose was 160 mg/dl (sensitivity 62% and specificity 68%), and 35.2% of the patients had increased levels. This group was elderly, had more prevalence of cardiovascular risk factors, worse renal function and GRACE score as well as more frequently Killip class ≥2. Treatment was similar in both groups besides less frequent use of clopidogrel in high glycaemic patients. The hyperglycaemia group had higher one-year mortality (17.2% vs. 5.6%, p<0.001). Moreover, binary blood glucose remained a predictor of death independently of the GRACE risk score and the presence of diabetes (odds ratio (OR) 1.99, 95% CI 1.40-2.84, p<0.001). The inclusion of blood glucose, as a continuous variable, in a logistic regression model with GRACE score, increased the area under the ROC curve from 0.80 to 0.82 (p=0.018) as well as the goodness-of-fit and was associated with an improvement in both the NRI (37%) and the IDI (0.021), suggesting effective reclassification. CONCLUSIONS: A blood glucose level on admission ≥ 160 mg/dl is an independent predictor of mortality in medium-term follow-up. It offers an incremental predictive value when added to the GRACE risk score, although with a modest magnitude of improvement, probably due to the high predictive performance of the GRACE risk score alone.info:eu-repo/semantics/publishedVersio

Is It Possible to Simplify Risk Stratification Scores for Patients with ST-Segment Elevation Myocardial Infarction Undergoing Primary Angioplasty?

INTRODUCTION: There are several risk scores for stratification of patients with ST-segment elevation myocardial infarction (STEMI), the most widely used of which are the TIMI and GRACE scores. However, these are complex and require several variables. The aim of this study was to obtain a reduced model with fewer variables and similar predictive and discriminative ability. METHODS: We studied 607 patients (age 62 years, SD=13; 76% male) who were admitted with STEMI and underwent successful primary angioplasty. Our endpoints were all-cause in-hospital and 30-day mortality. Considering all variables from the TIMI and GRACE risk scores, multivariate logistic regression models were fitted to the data to identify the variables that best predicted death. RESULTS: Compared to the TIMI score, the GRACE score had better predictive and discriminative performance for in-hospital mortality, with similar results for 30-day mortality. After data modeling, the variables with highest predictive ability were age, serum creatinine, heart failure and the occurrence of cardiac arrest. The new predictive model was compared with the GRACE risk score, after internal validation using 10-fold cross validation. A similar discriminative performance was obtained and some improvement was achieved in estimates of probabilities of death (increased for patients who died and decreased for those who did not). CONCLUSION: It is possible to simplify risk stratification scores for STEMI and primary angioplasty using only four variables (age, serum creatinine, heart failure and cardiac arrest). This simplified model maintained a good predictive and discriminative performance for short-term mortality

The Complexity of Graph-Based Reductions for Reachability in Markov Decision Processes

We study the never-worse relation (NWR) for Markov decision processes with an infinite-horizon reachability objective. A state q is never worse than a state p if the maximal probability of reaching the target set of states from p is at most the same value from q, regard- less of the probabilities labelling the transitions. Extremal-probability states, end components, and essential states are all special cases of the equivalence relation induced by the NWR. Using the NWR, states in the same equivalence class can be collapsed. Then, actions leading to sub- optimal states can be removed. We show the natural decision problem associated to computing the NWR is coNP-complete. Finally, we ex- tend a previously known incomplete polynomial-time iterative algorithm to under-approximate the NWR

A clinician’s guide to management of intra-abdominal hypertension and abdominal compartment syndrome in critically ill patients

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901

Ising model for distribution networks

An elementary Ising spin model is proposed for demonstrating cascading failures (break-downs, blackouts, collapses, avalanches, ...) that can occur in realistic networks for distribution and delivery by suppliers to consumers. A ferromagnetic Hamiltonian with quenched random fields results from policies that maximize the gap between demand and delivery. Such policies can arise in a competitive market where firms artificially create new demand, or in a solidary environment where too high a demand cannot reasonably be met. Network failure in the context of a policy of solidarity is possible when an initially active state becomes metastable and decays to a stable inactive state. We explore the characteristics of the demand and delivery, as well as the topological properties, which make the distribution network susceptible of failure. An effective temperature is defined, which governs the strength of the activity fluctuations which can induce a collapse. Numerical results, obtained by Monte Carlo simulations of the model on (mainly) scale-free networks, are supplemented with analytic mean-field approximations to the geometrical random field fluctuations and the thermal spin fluctuations. The role of hubs versus poorly connected nodes in initiating the breakdown of network activity is illustrated and related to model parameters

Predictive Impact on Medium-Term Mortality of Hematological Parameters in Acute Coronary Syndromes: Added Value on Top of GRACE Risk Score

BACKGROUND: Red Cell Distribution Width (RDW) prognostic value in patients with Acute Coronary Syndrome (ACS) has been well validated whereas that of Platelet Distribution Width (PDW) is less well known. OBJECTIVES: Investigate the incremental prognostic value, on top of GRACE risk score, of a new variable resulting from the combination of RDW and PDW. METHODS: Consecutive patients with ACS. Complete blood count, with RDW and PDW, was obtained. Primary endpoint was one-year all-cause mortality and Cox regression models were used to measure the influence of RDW and PDW on patients' survival time. A new combination categorical variable (RDW/PDW) was created with both discretized RDW and PDW and logistic regression models were used. Predictive value and discriminative ability of the model with GRACE risk score alone and of the model with inclusion of RDW/PDW was assessed. RESULTS: We included 787 patients. Hospital and one-year mortality rates were 5.1% and 7.8%, respectively. Both continuous RDW and PDW were independent predictors of death. The best cut-off for RDW was 13.9%, and 14.5% for PDW. Inclusion of RDW/PDW in a model with GRACE risk score improved the AUC from 0.81 (95% CI 0.75-0.86) to 0.84 (95% CI 0.79-0.90) (p=0.024) with an improvement in total NRI (56%) and IDI (0.048). CONCLUSIONS: Simple markers such as RDW and PDW can be useful in risk stratification of death after ACS. Combining both markers with GRACE risk score improved the predictive value for all-cause mortality and reduced the estimated risk of those who did not die.info:eu-repo/semantics/publishedVersio

A Self-Reference False Memory Effect in the DRM Paradigm: Evidence from Eastern and Western Samples

It is well established that processing information in relation to oneself (i.e., selfreferencing) leads to better memory for that information than processing that same information in relation to others (i.e., other-referencing). However, it is unknown whether self-referencing also leads to more false memories than other-referencing. In the current two experiments with European and East Asian samples, we presented participants the Deese-Roediger/McDermott (DRM) lists together with their own name or other people’s name (i.e., “Trump” in Experiment 1 and “Li Ming” in Experiment 2). We found consistent results across the two experiments; that is, in the self-reference condition, participants had higher true and false memory rates compared to those in the other-reference condition. Moreover, we found that selfreferencing did not exhibit superior mnemonic advantage in terms of net accuracy compared to other-referencing and neutral conditions. These findings are discussed in terms of theoretical frameworks such as spreading activation theories and the fuzzytrace theory. We propose that our results reflect the adaptive nature of memory in the sense that cognitive processes that increase mnemonic efficiency may also increase susceptibility to associative false memories

Prosocial Behaviour in Palliative Nurses: Psychometric Evaluation of the Prosociality Scale

Aim: The aim of this study was to examine the psychometric properties of a prosociality scale within the palliative nursing context, and then examine the impact of prosocial behaviour in relation to job and educational satisfaction among palliative nurses. Methods: An online cross-sectional survey was conducted in 25 Italian palliative care centres, with a total of 107 nurses completing the prosociality scale by Caprara et al (2005). Exploratory and confirmatory factor analyses were examined to evaluate a multidimensional model of prosociality. Results: A three-factor solution with a second order factor fitted the data well. The three dimensions extracted were labelled as helping, empathy, and sharing. Participants reported high levels of prosociality. In addition, prosociality was positively associated with job and educational satisfaction. Conclusions: The prosociality scale was valid and reliable when tested with palliative nurses. Although prosociality may be embedded in nurses’ personalities, this quality should be actively promoted to expand and improve the culture and the ethics of nursing