Day and night closed-loop control in adults with type 1 diabetes: a comparison of two closed-loop algorithms driving continuous subcutaneous insulin infusion versus patient self-management.

OBJECTIVE: To compare two validated closed-loop (CL) algorithms versus patient self-control with CSII in terms of glycemic control. RESEARCH DESIGN AND METHODS: This study was a multicenter, randomized, three-way crossover, open-label trial in 48 patients with type 1 diabetes mellitus for at least 6 months, treated with continuous subcutaneous insulin infusion. Blood glucose was controlled for 23 h by the algorithm of the Universities of Pavia and Padova with a Safety Supervision Module developed at the Universities of Virginia and California at Santa Barbara (international artificial pancreas [iAP]), by the algorithm of University of Cambridge (CAM), or by patients themselves in open loop (OL) during three hospital admissions including meals and exercise. The main analysis was on an intention-to-treat basis. Main outcome measures included time spent in target (glucose levels between 3.9 and 8.0 mmol/L or between 3.9 and 10.0 mmol/L after meals). RESULTS: Time spent in the target range was similar in CL and OL: 62.6% for OL, 59.2% for iAP, and 58.3% for CAM. While mean glucose level was significantly lower in OL (7.19, 8.15, and 8.26 mmol/L, respectively) (overall P = 0.001), percentage of time spent in hypoglycemia (<3.9 mmol/L) was almost threefold reduced during CL (6.4%, 2.1%, and 2.0%) (overall P = 0.001) with less time ≤2.8 mmol/L (overall P = 0.038). There were no significant differences in outcomes between algorithms. CONCLUSIONS: Both CAM and iAP algorithms provide safe glycemic control

MPC-based artificial pancreas: Strategies for individualization and meal compensation

Model-predictive control (MPC) algorithms have shown encouraging results for use in a closed-loop artificial pancreas system. This article describes a linear-MPC structure that can incorporate knowledge from conventional insulin therapy into a closed-loop AP

Method for controlling the delivery of insulin and the related system

A method (400) controls the delivery of insulin in a diabetic patient (P) based on data (d) representative of at least a fraction of a meal (m(k+i)) that the patient (P) will consume. The method provides from a block (R) representative of conventional therapy or open loop rule that the patient (P) is subject to, based on the data (d) representative of at least a fraction of the meal (m(k+i)), a reference insulin value (u0). The method is also based on data representative of the difference between input data (ŷ), a reference glycemic level, and feedback data (yCGM) representative of the glycemic level detected in the patient (P). A control module (301; 401) provides a value of insulin (i) to be delivered to the patient (P) based on the various representative data

MPC based Artificial Pancreas: Strategies for individualization and meal compensation

none6This paper addresses the design of glucose regulators based on Model Predictive Control (MPC) to be used as part of Artificial Pancreas devices for type 1 diabetic patients. Two key issues are deeply investigated: individualization, needed to cope with intersubject variability, and meal compensation, interpreted as a disturbance rejection problem. The individualization is achieved either by tuning the cost function, based on few well known clinical parameters (MPC1) or through the use of an individual model obtained via system identification techniques and an optimal tuning of the cost function based on real-life experiments (MPC2). The in silico tests, performed on 4 different scenarios using a simulator equipped with 100 patients, show that the performances of MPC1 are very promising, supporting its current use in an in vivo multicenter trial on 47 patients that is being carried out within the European Research Project AP@home. At the same time, further improvements are achieved by MPC2, showing that there is scope for in vivo experimentation of control strategies employing individually estimated patient models.noneP. Soru;G. De Nicolao;C. Toffanin;C. Dalla Man;C. Cobelli;L. MagniP., Soru; G., De Nicolao; C., Toffanin; DALLA MAN, Chiara; Cobelli, Claudio; L., Magn

MPC based Artificial Pancreas: Strategies for individualization and meal compensation

This paper addresses the design of glucose regulators based on Model Predictive Control (MPC) to be used as part of Artificial Pancreas devices for type 1 diabetic patients. Two key issues are deeply investigated: individualization, needed to cope with intersubject variability, and meal compensation, interpreted as a disturbance rejection problem. The individualization is achieved either by tuning the cost function, based on few well known clinical parameters (MPC1) or through the use of an individual model obtained via system identification techniques and an optimal tuning of the cost function based on real-life experiments (MPC2). The in silico tests, performed on 4 different scenarios using a simulator equipped with 100 patients, show that the performances of MPC1 are very promising, supporting its current use in an in vivo multicenter trial on 47 patients that is being carried out within the European Research Project AP@home. At the same time, further improvements are achieved by MPC2, showing that there is scope for in vivo experimentation of control strategies employing individually estimated patient models. (C) 2012 Elsevier Ltd. All rights reserved

First detection of the bloom forming Unruhdinium penardii (Dinophyceae) in a Mediterranean reservoir: insights on its ecology, morphology and genetics

13 pages, 5 figures, 2 tables, supplementary material https://doi.org/10.4081/aiol.2020.9500The freshwater genus Unruhdinium includes dinoflagellates hosting a tertiary diatom endosymbiont. Some of the species belonging to this genus form high-biomass blooms. In this study, data on the ecology, morphology and molecular identity of Unruhdinium penardii were reported for the first time from a Mediterranean reservoir (Cedrino Lake, Sardinia, Italy). The ecology of the species and its bloom events were examined along a multiannual series of data (2010-2017). Cell morphology was investigated using field samples and six cultures established by cell isolation. A molecular identification of the six strains was performed. Wild and cultured cells shared the same morphology, showing a prominent apical pore complex and two/three more or less prominent hypothecal spines as distinctive characters in light microscopy. Molecularly, the six cultured strains corresponded to the same taxonomic entity with sequences only differing in a few polymorphic positions for the studied markers SSU rDNA, LSU rDNA, ITS and endosymbiont SSU rDNA. All markers showed 99.5%−100% similarity with the available U. penardii sequences. Seasonality of U. penardii revealed its preference for the colder semester (from December to June) with bloom events restricted to late winter/early spring months. Three blooms resulting in reddish water discolorations were observed along the study period (2011, 2012 and 2017). GLMs revealed a significant role of water depth, temperature, and reactive phosphorous in determining the highest cell densities (>5 x 104 cells L-1). The results obtained contribute to the increase of field ecology knowledge on this species, demonstrating it is well established in the Mediterranean area, and being able to produce recurrent high biomass blooms in the studied reservoiThe activities of Prof Antonella Lugliè and Dr. Mario Padedda were supported by the research fund of the University of Sassari (Fondo di Ateneo per la Ricerca 2019).With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)Peer reviewe

Trophic State and Toxic Cyanobacteria Density in Optimization Modeling of Multi-Reservoir Water Resource Systems

The definition of a synthetic index for classifying the quality of water bodies is a key aspect in integrated planning and management of water resource systems. In previous works [1,2], a water system optimization modeling approach that requires a single quality index for stored water in reservoirs has been applied to a complex multi-reservoir system. Considering the same modeling field, this paper presents an improved quality index estimated both on the basis of the overall trophic state of the water body and on the basis of the density values of the most potentially toxic Cyanobacteria. The implementation of the index into the optimization model makes it possible to reproduce the conditions limiting water use due to excessive nutrient enrichment in the water body and to the health hazard linked to toxic blooms. The analysis of an extended limnological database (1996–2012) in four reservoirs of the Flumendosa-Campidano system (Sardinia, Italy) provides useful insights into the strengths and limitations of the proposed synthetic index

Day and night closed-loop control in adults with type 1 diabetes: a comparison of two closed-loop algorithms driving continuous subcutaneous insulin infusion versus patient self-management.

OBJECTIVE: To compare two validated closed-loop (CL) algorithms versus patient self-control with CSII in terms of glycemic control. RESEARCH DESIGN AND METHODS: This study was a multicenter, randomized, three-way crossover, open-label trial in 48 patients with type 1 diabetes mellitus for at least 6 months, treated with continuous subcutaneous insulin infusion. Blood glucose was controlled for 23 h by the algorithm of the Universities of Pavia and Padova with a Safety Supervision Module developed at the Universities of Virginia and California at Santa Barbara (international artificial pancreas [iAP]), by the algorithm of University of Cambridge (CAM), or by patients themselves in open loop (OL) during three hospital admissions including meals and exercise. The main analysis was on an intention-to-treat basis. Main outcome measures included time spent in target (glucose levels between 3.9 and 8.0 mmol/L or between 3.9 and 10.0 mmol/L after meals). RESULTS: Time spent in the target range was similar in CL and OL: 62.6% for OL, 59.2% for iAP, and 58.3% for CAM. While mean glucose level was significantly lower in OL (7.19, 8.15, and 8.26 mmol/L, respectively) (overall P = 0.001), percentage of time spent in hypoglycemia (<3.9 mmol/L) was almost threefold reduced during CL (6.4%, 2.1%, and 2.0%) (overall P = 0.001) with less time ≤2.8 mmol/L (overall P = 0.038). There were no significant differences in outcomes between algorithms. CONCLUSIONS: Both CAM and iAP algorithms provide safe glycemic control

Blood Bacterial DNA Load and Profiling Differ in Colorectal Cancer Patients Compared to Tumor-Free Controls

Inflammation and immunity are linked to intestinal adenoma (IA) and colorectal cancer (CRC) development. The gut microbiota is associated with CRC risk. Epithelial barrier dysfunction can occur, possibly leading to increased intestinal permeability in CRC patients. We conducted a case-control study including 100 incident histologically confirmed CRC cases, and 100 IA and 100 healthy subjects, matched to cases by center, sex and age. We performed 16S rRNA gene analysis of blood and applied conditional logistic regression. Further analyses were based on negative binomial distribution normalization and Random Forest algorithm. We found an overrepresentation of blood 16S rRNA gene copies in colon cancer as compared to tumor-free controls. For high levels of gene copies, community diversity was higher in colon cancer cases than controls. Bacterial taxa and operational taxonomic unit abundances were different between groups and were able to predict CRC with an accuracy of 0.70. Our data support the hypothesis of a higher passage of bacteria from gastrointestinal tract to bloodstream in colon cancer. This result can be applied on non-invasive diagnostic tests for colon cancer control

Day and Night Closed-Loop Control in Adults With Type 1 Diabetes Mellitus A comparison of two closed-loop algorithms driving continuous subcutaneous insulin infusion versus patient self-management LUTZ HEINEMANN, PHD 9 ON BEHALF OF THE AP@HOME CONSORTIUM

OBJECTIVEdTo compare two validated closed-loop (CL) algorithms versus patient selfcontrol with CSII in terms of glycemic control. RESEARCH DESIGN AND METHODSdThis study was a multicenter, randomized, three-way crossover, open-label trial in 48 patients with type 1 diabetes mellitus for at least 6 months, treated with continuous subcutaneous insulin infusion. Blood glucose was controlled for 23 h by the algorithm of the Universities of Pavia and Padova with a Safety Supervision Module developed at the Universities of Virginia and California at Santa Barbara (international artificial pancreas [iAP]), by the algorithm of University of Cambridge (CAM), or by patients themselves in open loop (OL) during three hospital admissions including meals and exercise. The main analysis was on an intention-totreat basis. Main outcome measures included time spent in target (glucose levels between 3.9 and 8.0 mmol/L or between 3.9 and 10.0 mmol/L after meals). RESULTSdTime spent in the target range was similar in CL and OL: 62.6% for OL, 59.2% for iAP, and 58.3% for CAM. While mean glucose level was significantly lower in OL (7.19, 8.27, and 8.26 mmol/L, respectively) (overall P = 0.001), percentage of time spent in hypoglycemia (,3.9 mmol/L) was almost threefold reduced during CL (6.4%, 2.1%, and 2.0%) (overall P = 0.001) with less time #2.8 mmol/L (overall P = 0.038). There were no significant differences in outcomes between algorithms. CONCLUSIONSdBoth CAM and iAP algorithms provide safe glycemic control