Fully Integrated Artificial Pancreas in Type 1 Diabetes: Modular Closed-Loop Glucose Control Maintains Near Normoglycemia

Integrated closed-loop control (CLC), combining continuous glucose monitoring (CGM) with insulin pump (continuous subcutaneous insulin infusion [CSII]), known as artificial pancreas, can help optimize glycemic control in diabetes. We present a fundamental modular concept for CLC design, illustrated by clinical studies involving 11 adolescents and 27 adults at the Universities of Virginia, Padova, and Montpellier. We tested two modular CLC constructs: standard control to range (sCTR), designed to augment pump plus CGM by preventing extreme glucose excursions; and enhanced control to range (eCTR), designed to truly optimize control within near normoglycemia of 3.9-10 mmol/L. The CLC system was fully integrated using automated data transfer CGM→algorithm→CSII. All studies used randomized crossover design comparing CSII versus CLC during identical 22-h hospitalizations including meals, overnight rest, and 30-min exercise. sCTR increased significantly the time in near normoglycemia from 61 to 74%, simultaneously reducing hypoglycemia 2.7-fold. eCTR improved mean blood glucose from 7.73 to 6.68 mmol/L without increasing hypoglycemia, achieved 97% in near normoglycemia and 77% in tight glycemic control, and reduced variability overnight. In conclusion, sCTR and eCTR represent sequential steps toward automated CLC, preventing extremes (sCTR) and further optimizing control (eCTR). This approach inspires compelling new concepts: modular assembly, sequential deployment, testing, and clinical acceptance of custom-built CLC systems tailored to individual patient needs.     

Vertical Transmission of SARS-CoV-2 in Second Trimester Associated with Severe Neonatal Pathology

The effects of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in women on the gestation course and the health of the fetus, particularly in the first and second trimesters, remain very poorly explored. This report describes a case in which the normal development of pregnancy was complicated immediately after the patient had experienced Coronavirus disease 2019 (COVID-19) at the 21st week of gestation. Specific conditions included critical blood flow in the fetal umbilical artery, fetal growth restriction (1st percentile), right ventricular hypertrophy, hydropericardium, echo-characteristics of hypoxic-ischemic brain injury (leukomalacia in periventricular area) and intraventricular hemorrhage at the 25th week of gestation. Premature male neonate delivered at the 26th week of gestation died after 1 day 18 h due to asystole. The results of independent polymerase chain reaction (PCR), mass spectrometry and immunohistochemistry analyses of placenta tissue, umbilical cord blood and child blood jointly indicated vertical transmission of SARS–CoV-2 from mother to the fetus, which we conclude to be the major cause for the development of maternal vascular malperfusion in the studied case.     

Evaluation of humoral response to tumor antigens using recombinant expression-based serological mini-arrays (SMARTA)

Screening of expression cDNA libraries derived from human neoplasms with autologous sera (SEREX) is an established method for defining antigens immunogenic in individual cancer patients. Although the majority of SEREX-derived cDNA clones encode autoantigens, some of them represent shared cancer antigens with cancer-related serological profiles. Routine evaluation of multiple SEREX-derived clones in serological assays using panels of allogeneic sera from cancer patients is an important step towards defining disease parameters of diagnostic and prognostic significance. Here we show how the seroreactivity of multiple SEREX-derived antigens can be simultaneously evaluated using a rapid semi-quantitative protocol of allogeneic screening, which we call SMARTA (serological mini-arrays of recombinant tumor antigens).     

P2X receptor-mediated excitatory synaptic currents in somatosensory cortex

Fast P2X receptor-mediated excitatory postsynaptic current (EPSC) was found in pyramidal neurones of layer V of somatosensory cortex in slices acutely isolated from the brain of 17- to 22-day-old rats. The EPSCs were elicited by field electrical stimulation in the layer VI at 0.1 Hz in the presence of picrotoxin. When the glutamatergic EPSC was blocked by glutamate receptors inhibitors NBQX and D-AP5, a residual EPSC (rEPSC) was recorded from 85% of neurones tested. This rEPSC was not affected by blockers of nicotinic (hexamethonium) and serotonin (Y25130) receptors; however, it was reversibly inhibited by P2X receptors antagonists (NF023, NF279, and PPADS). An application of ATP (20 microM), beta,gamma-methylene ATP (25 microM), and alpha,beta-methylene ATP (20 microM) to acutely isolated pyramidal neurones of layer V evoked inward currents (30 to 400 pA) in 75% of cells tested. We concluded that several subtypes of P2X purinoreceptors participate in synaptic transmission in neocortex.     

Superfluid transition of homogeneous and trapped two-dimensional Bose gases

Current experiments on atomic gases in highly anisotropic traps present the opportunity to study in detail the low temperature phases of two-dimensional inhomogeneous systems. Although, in an ideal gas, the trapping potential favors Bose-Einstein condensation at finite temperature, interactions tend to destabilize the condensate, leading to a superfluid Kosterlitz-Thouless-Berezinskii phase with a finite superfluid mass density but no long-range order, as in homogeneous fluids. The transition in homogeneous systems is conveniently described in terms of dissociation of topological defects (vortex-antivortex pairs). However, trapped two-dimensional gases are more directly approached by generalizing the microscopic theory of the homogeneous gas. In this paper, we first derive, via a diagrammatic expansion, the scaling structure near the phase transition in a homogeneous system, and then study the effects of a trapping potential in the local density approximation. We find that a weakly interacting trapped gas undergoes a Kosterlitz-Thouless-Berezinskii transition from the normal state at a temperature slightly below the Bose-Einstein transition temperature of the ideal gas. The characteristic finite superfluid mass density of a homogeneous system just below the transition becomes strongly suppressed in a trapped gas.     

Artificial Pancreas: Closed-Loop Control of Glucose Variability in Diabetes: Model Predictive Control of Type 1 Diabetes: An in Silico Trial

Background

The development of artificial pancreas has received a new impulse from recent technological advancements in subcutaneous continuous glucose monitoring and subcutaneous insulin pump delivery systems. However, the availability of innovative sensors and actuators, although essential, does not guarantee optimal glycemic regulation. Closed-loop control of blood glucose levels still poses technological challenges to the automatic control expert, most notable of which are the inevitable time delays between glucose sensing and insulin actuation.

Methods

A new in silico model is exploited for both design and validation of a linear model predictive control (MPC) glucose control system. The starting point is a recently developed meal glucose–insulin model in health, which is modified to describe the metabolic dynamics of a person with type 1 diabetes mellitus. The population distribution of the model parameters originally obtained in healthy 204 patients is modified to describe diabetic patients. Individual models of virtual patients are extracted from this distribution. A discrete-time MPC is designed for all the virtual patients from a unique input–output-linearized approximation of the full model based on the average population values of the parameters. The in silico trial simulates 4 consecutive days, during which the patient receives breakfast, lunch, and dinner each day.

Results

Provided that the regulator undergoes some individual tuning, satisfactory results are obtained even if the control design relies solely on the average patient model. Only the weight on the glucose concentration error needs to be tuned in a quite straightforward and intuitive way. The ability of the MPC to take advantage of meal announcement information is demonstrated. Imperfect knowledge of the amount of ingested glucose causes only marginal deterioration of performance. In general, MPC results in better regulation than proportional integral derivative, limiting significantly the oscillation of glucose levels.

Conclusions

The proposed in silico trial shows the potential of MPC for artificial pancreas design. The main features are a capability to consider meal announcement information, delay compensation, and simplicity of tuning and implementation.