Artificial pancreas treatment for outpatients with type 1 diabetes: systematic review and meta-analysis.

OBJECTIVE: To evaluate the efficacy and safety of artificial pancreas treatment in non-pregnant outpatients with type 1 diabetes. DESIGN: Systematic review and meta-analysis of randomised controlled trials. DATA SOURCES: Medline, Embase, Cochrane Library, and grey literature up to 2 February 2018. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomised controlled trials in non-pregnant outpatients with type 1 diabetes that compared the use of any artificial pancreas system with any type of insulin based treatment. Primary outcome was proportion (%) of time that sensor glucose level was within the near normoglycaemic range (3.9-10 mmol/L). Secondary outcomes included proportion (%) of time that sensor glucose level was above 10 mmol/L or below 3.9 mmol/L, low blood glucose index overnight, mean sensor glucose level, total daily insulin needs, and glycated haemoglobin. The Cochrane Collaboration risk of bias tool was used to assess study quality. RESULTS: 40 studies (1027 participants with data for 44 comparisons) were included in the meta-analysis. 35 comparisons assessed a single hormone artificial pancreas system, whereas nine comparisons assessed a dual hormone system. Only nine studies were at low risk of bias. Proportion of time in the near normoglycaemic range (3.9-10.0 mmol/L) was significantly higher with artificial pancreas use, both overnight (weighted mean difference 15.15%, 95% confidence interval 12.21% to 18.09%) and over a 24 hour period (9.62%, 7.54% to 11.7%). Artificial pancreas systems had a favourable effect on the proportion of time with sensor glucose level above 10 mmol/L (-8.52%, -11.14% to -5.9%) or below 3.9 mmol/L (-1.49%, -1.86% to -1.11%) over 24 hours, compared with control treatment. Robustness of findings for the primary outcome was verified in sensitivity analyses, by including only trials at low risk of bias (11.64%, 9.1% to 14.18%) or trials under unsupervised, normal living conditions (10.42%, 8.63% to 12.2%). Results were consistent in a subgroup analysis both for single hormone and dual hormone artificial pancreas systems. CONCLUSIONS: Artificial pancreas systems are an efficacious and safe approach for treating outpatients with type 1 diabetes. The main limitations of current research evidence on artificial pancreas systems are related to inconsistency in outcome reporting, small sample size, and short follow-up duration of individual trials

Metabolic syndrome in overweight and obese children and adolescents

Metabolic syndrome (MS) is defined as clustering of cardiovascular risk factors with the common pathophysiology of abdominal obesity and insulin resistance. The prevalence and characteristics of MS in children and adolescents have not been extensively studied. Furthermore, its relationship with sub-clinical inflammation, non-alcoholic fatty liver disease (NAFLD) and premature atheromatosis in youth remains to be elucidated. The aim of this study was: 1. To define the prevalence and characteristics of MS in overweight and obese children and adolescents. 2. To diagnose children with prediabetes, hyperinsulinemia, insulin resistance and NAFLD. 3. To investigate the hypothesis that obese and overweight children with MS, compared to their counterparts without metabolic abnormalities, have elevated levels of well established markers of sub-clinical inflammation such as hsCRP, IL-6, TNFa, fibrinogen, adiponectin and homocysteine and run therefore increased cardiovascular risk. A total of 144 children and adolescents, 6-17 year old, were enrolled in this study, classified according to their BMI into three groups. Group A: 54 obese (BMI≥95th PC) children and adolescents (28 female). Group Β: 50 overweight (85th PC ≤ΒΜΙ20 μU/ml. MS was diagnosed in 31.5% of the obese and in 8% of the overweight children and adolescents. Low HDL-cholesterol and increased triglycerides were the main determinants of the syndrome both in obese (94% and 64.7%, respectively) and overweight (75% each) children and adolescents. Prediabetes (IFG or/and IGT) was diagnosed in 44.4% of the obese and 24% of the overweight children and adolescents. More specifically, 29.6% of the obese and 16% of the overweight children and adolescents had IFG, while the percentage of the obese and overweight children and adolescents with IGΤ was 5.6% και 6% respectively. 9.3% of the obese and 2% of the overweight children and adolescents had both IFG and IGT. NAFLD was diagnosed in 44.4% of the obese and in 18% of the overweight children and adolescents. 79.6% of the obese και το 56% of the overweight children and adolescents were insulin resistant. Moreover, 55.6% of the obese and 34% of the overweight children and adolescents were huperinsulinemic. Obese and overweight children with MS compared to their counterparts without MS had more severe abdominal obesity (WC: 102.0±12.5cm vs 93.2±9.2cm, p=0.005), were more insulin resistant (HOMA-IR: 7.6±5.0 vs 4.5±2.7, p=0.012), had elevated fasting glucose (FG: 100.0±9.7mg/dl vs 94.6±8.7mg/dl, p=0.015), had more atherogenic lipid profile (HDL: 36±7mg/dl vs 48±8mg/dl, p3.1. Ως υπερινσουλιναιμία ορίστηκε η τιμή ινσουλίνης νηστείας>20μU/ml. Το ΜΣ διαγνώστηκε στο 31.5% των παχύσαρκων και στο 8% των υπέρβαρων παιδιών και εφήβων. Η χαμηλή HDL-χοληστερόλη και τα αυξημένα τριγλυκερίδια αποτέλεσαν τις συχνότερες συνιστώσες του ΜΣ τόσο στην ομάδα των παχύσαρκων (94% και 64.7% αντίστοιχα), όσο και στην ομάδα των υπέρβαρων (75% για καθεμιά) παιδιών και εφήβων. Προδιαβήτης (IFG ή/και IGT) διαγνώστηκε στο 44.4% των παχύσαρκων και στο 24% των υπέρβαρων παιδιών και εφήβων. Ειδικότερα το 29.6% των παχύσαρκων και το 16% των υπέρβαρων παιδιών και εφήβων παρουσίασαν IFG, ενώ τα ποσοστά των παχύσαρκων και υπέρβαρων παιδιών και εφήβων με IGΤ ήταν αντίστοιχα 5.6% και 6%. Το 9.3% των παχύσαρκων και το 2% των υπέρβαρων παιδιών και εφήβων παρουσίαζαν ταυτόχρονα IFG και IGT. Η NAFLD διαγνώστηκε στο 44.4% των παχύσαρκων και στο 18% των υπέρβαρων παιδιών και εφήβων. Το 79.6% των παχύσαρκων και το 56% των υπέρβαρων παιδιών και εφήβων παρουσίαζαν αντίσταση στην ινσουλίνη, ενώ το 55.6% των παχύσαρκων και το 34% των υπέρβαρων παιδιών και εφήβων παρουσίαζαν υπερινσουλιναιμία. Από τη σύγκριση παχύσαρκων και υπέρβαρων παιδιών με και χωρίς ΜΣ διαπιστώθηκε ότι η παρουσία ΜΣ σχετίζεται με αυξημένα επίπεδα κοιλιακής παχυσαρκίας (ΠΜ: 102.0±12.5cm vs 93.2±9.2cm, p=0.005), βαρύτερη ινσουλινοαντίσταση (HOMA-IR: 7.6±5.0 vs 4.5±2.7, p=0.012), υπεργλυκαιμία νηστείας (ΓΝ: 100.0±9.7mg/dl vs 94.6±8.7mg/dl, p=0.015), αθηρογόνο λιπιδαιμικό προφίλ (HDL: 36±7mg/dl vs 48±8mg/dl, p<0.001) και τριγλυκερίδια: 137±69 mg/dl vs 83±32mg/dl, p=0.002) και αυξημένους δείκτες υποκλινικής φλεγμονής (ινωδογόνο: 446±91mg/dl vs 389±94mg/dl, p=0.016 και IL-6: 2.9±1.9 vs1.7±1.5, p=0.013). Συμπερασματικά, στην παρούσα μελέτη το ΜΣ βρέθηκε ιδιαίτερα συχνό στα παχύσαρκα παιδιά και εφήβους με κύριες συνιστώσες τα χαμηλά επίπεδα HDL-χοληστερόλης και τα αυξημένα τριγλυκερίδια. Επιπλέον ένα σημαντικό ποσοστό υπέρβαρων και παχύσαρκων παιδιών παρουσιάζουν προδιαβήτη, κυρίως με τη μορφή IFG, και NAFLD. Από τη σύγκριση παχύσαρκων και υπέρβαρων παιδιών με και χωρίς ΜΣ διαπιστώθηκε ότι η παρουσία ΜΣ σχετίζεται με εξεσημασμένη κοιλιακή παχυσαρκία, βαριά ινσουλινοαντίσταση, υπεργλυκαιμία, αθηρογόνο λιπιδαιμικό προφίλ και υποκλινική φλεγμονή, όπως εκφράζεται με τα αυξημένα επίπεδα ινωδογόνου και IL-6. Κατά συνέπεια παιδιά με ΜΣ ίσως θα πρέπει να αποτελέσουν επίκεντρο περισσότερο εντατικοποιημένης παρέμβασης συγκριτικά με εκείνα με απλή παχυσαρκία, καθώς φαίνεται να διατρέχουν αυξημένο κίνδυνο καρδιαγγειακής νόσου στην ενήλικη ζωή

Emulating Artificial Synaptic Plasticity Characteristics from SiO2-Based Conductive Bridge Memories with Pt Nanoparticles

The quick growth of information technology has necessitated the need for developing novel electronic devices capable of performing novel neuromorphic computations with low power consumption and a high degree of accuracy. In order to achieve this goal, it is of vital importance to devise artificial neural networks with inherent capabilities of emulating various synaptic properties that play a key role in the learning procedures. Along these lines, we report here the direct impact of a dense layer of Pt nanoparticles that plays the role of the bottom electrode, on the manifestation of the bipolar switching effect within SiO2-based conductive bridge memories. Valuable insights regarding the influence of the thermal conductivity value of the bottom electrode on the conducting filament growth mechanism are provided through the application of a numerical model. The implementation of an intermediate switching transition slope during the SET transition permits the emulation of various artificial synaptic functionalities, such as short-term plasticity, including paired-pulsed facilitation and paired-pulse depression, long-term plasticity and four different types of spike-dependent plasticity. Our approach provides valuable insights toward the development of multifunctional synaptic elements that operate with low power consumption and exhibit biological-like behavior

Credit card application assessment using a neuro- fuzzy classification system

Summarization: Credit cards constitute one of the most common forms of consumer loans. The main purpose of this paper is to apply fuzzy data analysis to the credit scoring problem. A neuro-fuzzy classification technique is compared to the logis- tic regression approach and novel machine learning algorithms that are currently being investigated as credit scoring methods. The 10-fold cross-validation procedure is performed to analyze the generalization properties and the robustness of the developed models. Neuro-fuzzy classification sys- tems allow for prior knowledge to be imbedded in the analysis and utilize human expertise in the form of fuzzy if then rules to provide an insight into the reasoning mechanism behind the credit approval/rejection decision. This feature is particularly useful in financial applications such as credit granting, where credit analysts should be in a position to provide an explanation for their decisionsPresented on

Renewable Energy Sources, the Internet of Things and the Third Industrial Revolution: Smart Grid and Contemporary Information and Communication Technologies

International audienc

A Rare Case of Disseminated Pyogenic Gonococcal Infection in an Immunocompetent Woman

We present a case of previously healthy, immunocompetent, 41-year-old woman who developed systemic inflammatory response syndrome secondary to Neisseria gonorrhoeae bacteremia. Clinical course was complicated by the simultaneous formation of multiple muscular abscesses, epidural abscess, and septic spondylodiscitis. The patient responded well to prolonged ceftriaxone treatment and was released 10 weeks after initial admission. Spinal lesions and/or pyomyositis individually constitute rare complications of disseminated gonococcal infection. This case, combining both manifestations, is to our knowledge unique. Apropos, diversity of the clinical presentation, and therapeutic challenges for this historical disease are discussed for the practicing physician

Unconventional memristive nanodevices

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.One of the most enticing candidates for next-generation computing systems is the memristor. Memristor-based novel architectures have demonstrated considerable promise in replacing or augmenting traditional computing platforms based on the Von Neumann architecture, which faces many issues in the big-data era, as well as in newly developed neuromorphic tasks. Although the current classical computing architecture is unlikely to be abandoned in the foreseeable future, the growing trend of neuromorphic, quantum, and bio-inspired computing schemes calls for more specialized beyond Von Neumann platforms. Memristors showcase multiple advantages in terms of small area footprint, energy efficiency, high endurance, bio-compatibility, and their inherent synaptic and neuromorphic behavior. The topic of this work is to present the memristive devices that meet the requirements for the implementation of the novel beyond Von Neumann applications and examine their switching mechanism and material selection, as well as to conduct a performance comparison between the fabricated devices paving the way for future computing applications.Postprint (author's final draft

Unconventional computing with memristive nanocircuits

Computing demands are growing rapidly as bigdata and artificial intelligence applications become increasingly tasking. Bio-inspired and quantum-based techniques are proving to be quite promising for the development of novel circuits and systems. These systems can contribute to the resolution of a wider variety of problems while also providing improvements to existing techniques. As the von Neumann architecture’s expected performance, which has been dominant for the past several decades, is now hindered by physical limitations, novel computing architectures, assisted by novel materials and circuit devices, are starting to emerge and provide promising results. The topic of this work is to examine the memory and computing capabilities of emergent memristor-based nanocircuits and demonstrate their advantages compared to their classical counterparts.Postprint (author's final draft