External validation of a prediction model for estimating fat mass in children and adolescents in 19 countries: individual participant data meta-analysis

Objective To evaluate the performance of a UK based prediction model for estimating fat-free mass (and indirectly fat mass) in children and adolescents in non-UK settings. Design Individual participant data meta-analysis. Setting 19 countries. Participants 5693 children and adolescents (49.7% boys) aged 4 to 15 years with complete data on the predictors included in the UK based model (weight, height, age, sex, and ethnicity) and on the independently assessed outcome measure (fat-free mass determined by deuterium dilution assessment). Main outcome measures The outcome of the UK based prediction model was natural log transformed fat-free mass (lnFFM). Predictive performance statistics of R2, calibration slope, calibration-in-the-large, and root mean square error were assessed in each of the 19 countries and then pooled through random effects meta-analysis. Calibration plots were also derived for each country, including flexible calibration curves. Results The model showed good predictive ability in non-UK populations of children and adolescents, providing R2 values of >75% in all countries and >90% in 11 of the 19 countries, and with good calibration (ie, agreement) of observed and predicted values. Root mean square error values (on fat-free mass scale) were <4 kg in 17 of the 19 settings. Pooled values (95% confidence intervals) of R2, calibration slope, and calibration-in-the-large were 88.7% (85.9% to 91.4%), 0.98 (0.97 to 1.00), and 0.01 (−0.02 to 0.04), respectively. Heterogeneity was evident in the R2 and calibration-in-the-large values across settings, but not in the calibration slope. Model performance did not vary markedly between boys and girls, age, ethnicity, and national income groups. To further improve the accuracy of the predictions, the model equation was recalibrated for the intercept in each setting so that country specific equations are available for future use. Conclusion The UK based prediction model, which is based on readily available measures, provides predictions of childhood fat-free mass, and hence fat mass, in a range of non-UK settings that explain a large proportion of the variability in observed fat-free mass, and exhibit good calibration performance, especially after recalibration of the intercept for each population. The model demonstrates good generalisability in both low-middle income and high income populations of healthy children and adolescents aged 4-15 years

Prevalence of Brugada-type ECG pattern and early ventricular repolarization pattern in Tunisian athletes

Sana Ouali1, Helmi Ben Salem1, Sami Hammas1, Elyes Neffeti1, Fahmi Remedi1, Abdallah Mahdhaoui2, Essia Boughzela1, Rafik Mankai31Department of Cardiology, Sahloul Hospital, Sousse, Tunisia; 2Department of Cardiology, Farhat Hached, Sousse, Tunisia; 3Central Sports Medicine Centre of El Menzah, TunisiaIntroduction: No data regarding the prevalence of the Brugada-type electrocardiogram (ECG) pattern and the early ventricular repolarization pattern (ERP) in the North African population were available. The aims of this study were to determine the frequency of Brugada-type ECG pattern and ERP in Tunisia and to evaluate ECG descriptors of ventricular repolarization in a population of athletes.Methods: Over a 2-year period, resting 12-lead ECG recordings were analyzed from athletes (n = 540; 348 males; age 18.3 &amp;plusmn; 2.4 years). Brugada-type ECG pattern was defined as Type 1, 2, or 3, and ERP was characterized by an elevation of the J point in the inferior and/or lateral leads. The population was divided into three groups of athletes: ERP group; Brugada-type ECG pattern group; and control group, with neither ERP nor Brugada ECG pattern. Clinical and electrocardiographic parameters were compared among the study groups.Results: Nine subjects (1.66%) had a Brugada-type ECG pattern. None of them had the coved-type, 3 (0.6%) had the Type 2, and 6 (1.1%) had the Type 3. All subjects were asymptomatic. A Brugada-type ECG pattern was observed in seven males. No female had the Type 2 Brugada ECG pattern. ECG parameters were similar among Brugada-type ECG pattern and control athletes. ERP (119 subjects, 22%) was obtained in 98 males. Heart rate was lower, the QRS duration shorter and QT and Tpeak&amp;ndash;Tend intervals were longer in ERP than control groups.Conclusion: The results indicate that the frequency of the Brugada-type ECG pattern and ERP were respectively 1.66% and 22.00% in athletes, being more prevalent in males. The ERP group experienced shorter QRS duration and longer Tpeak&amp;ndash;Tend interval than in the control population.Keywords: J wave, ERP athletes, T wav

Synergistic antifungal activity and potential mechanism of action of a glycolipid like compound produced by Streptomyces blastmyceticus S108 against Candida clinical isolates

Ayed A, Essid R, Mankai H, et al. Synergistic antifungal activity and potential mechanism of action of a glycolipid like compound produced by Streptomyces blastmyceticus S108 against Candida clinical isolates. Journal of Applied Microbiology . 2023: lxad246.AIM: The present study aimed to investigate a novel antifungal compound produced by Streptomyces blastmyceticus S108 strain. Its effectiveness against clinical isolates of Candida species and its synergistic effect with conventional antifungal drugs were assessed and its molecular mechanism of action was further studied against C. albicans.; METHODS AND RESULTS: A newly isolated strain from Tunisian soil, Streptomyces blastmyceticus S108, showed significant antifungal activity against Candida species by well diffusion method. The butanolic extract of S108 strain supernatant exhibited the best anti-Candida activity with a minimal inhibitory concentration (MIC) value of 250 mug mL-1, determined by the microdilution method. The bio-guided purification steps of the butanolic extract were performed by chromatographic techniques. Among the fractions obtained, F13 demonstrated the highest level of activity, displaying a MIC of 31.25 mug mL-1. Gas Chromatography-Mass Spectrometry (GC-MS) and Electrospray Ionisation Mass Spectrometry (ESI-MS) analyses of this fraction (F13) revealed the glycolipidic nature of the active molecule with a molecular weight of 685.6 m/z. This antifungal metabolite remained stable to physicochemical changes and did not show hemolytic activity even at 4 MIC corresponding to 125 g mL-1 towards human erythrocytes. Besides, the glycolipid compound was combined with 5-flucytosine and showed a high synergistic effect with a FICI value 0.14 against C. albicans ATCC 10231. This combination resulted in a decrease of MIC values of 5-flucytosine and the glycolipid-like compound by 8 and 64-fold, respectively. The examination of gene expression in treated Candida albicans cells by qPCR revealed that the active compound tested alone or in combination with 5-flucytosine blocks the ergosterol biosynthesis pathway by down regulating the expression of ERG1, ERG3, ERG5, ERG11 and ERG25 genes.; CONCLUSION AND IMPACT OF THE STUDY: The new glycolipid like compound, produced by Streptomyces S108 isolate, could be a promising drug for medical use against pathogenic Candida isolates. © The Author(s) 2023. Published by Oxford University Press on behalf of Applied Microbiology International

A Data Classification Method for Inconsistency and Incompleteness Detection in Access Control Policy Sets

Access control policies may contain anomalies such as incompleteness and inconsistency, which can result in security vulnerabilities. Detecting such anomalies in large sets of complex policies automatically is a difficult and challenging problem. In this paper, we propose a novel method for detecting inconsistency and incompleteness in access control policies with the help of data classification tools well known in data mining. Our proposed method consists of three phases: firstly, we perform parsing on the policy data set; this includes ordering of attributes and normalization of Boolean expressions. Secondly, we generate decision trees with the help of our proposed algorithm, which is a modification of the well-known C4.5 algorithm. Thirdly, we execute our proposed anomaly detection algorithm on the resulting decision trees. The results of the anomaly detection algorithm are presented to the policy administrator who will take remediation measures. In contrast to other known policy validation methods, our method provides means for handling incompleteness, continuous values and complex Boolean expressions. In order to demonstrate the efficiency of our method in discovering inconsistencies, incompleteness and redundancies in access control policies, we also provide a proof-of-concept implementation

Hematopoietic Stem Cell Heterogeneity Is Linked to the Initiation and Therapeutic Response of Myeloproliferative Neoplasms.

The implications of stem cell heterogeneity for disease pathogenesis and therapy are poorly defined. JAK2V617F+ myeloproliferative neoplasms (MPNs), harboring the same mutation in hematopoietic stem cells (HSCs), display diverse phenotypes, including polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). These chronic malignant disorders are ideal models to analyze the pathological consequences of stem cell heterogeneity. Single-cell gene expression profiling with parallel mutation detection demonstrated that the megakaryocyte (Mk)-primed HSC subpopulation expanded significantly with enhanced potential in untreated individuals with JAK2V617F+ ET, driven primarily by the JAK2 mutation and elevated interferon signaling. During treatment, mutant HSCs were targeted preferentially in the Mk-primed HSC subpopulation. Interestingly, homozygous mutant HSCs were forced to re-enter quiescence, whereas their heterozygous counterparts underwent apoptosis. This study provides important evidence for the association of stem cell heterogeneity with the pathogenesis and therapeutic response of a malignant disease