Exercise-induced growth hormone response in euglycaemia and hyperglycaemia in patients with Type 1 diabetes mellitus

To compare exercise-induced growth hormone (GH) response in patients with Type 1 diabetes during stable euglycaemic and hyperglycaemic conditions.

Response of interleukin-6 during euglycaemic and hyperglycaemic exercise in patients with type 1 diabetes mellitus

The aim of this randomized, single-blinded cross-over study was to investigate the response of interleukin-6 (IL-6) during moderate aerobic exercise in stable euglycaemia and hyperglycaemia in seven male patients with type 1 diabetes mellitus. IL-6 increased significantly over the entire study period in euglycaemia, but not in hyperglycaemia.

Pro-inflammatory biomarkers during experimental gingivitis in patients with type 1 diabetes mellitus: a proof-of-concept study

To compare gingival crevicular fluid (GCF) biomarker levels and microbial distribution in plaque biofilm (SP) samples for subjects with type 1 diabetes (T1DM) versus healthy subjects without diabetes during experimental gingivitis (EG).

Noninvasive assessment of exercise-related intramyocellular acetylcarnitine in euglycemia and hyperglycemia in patients with type 1 diabetes using ¹H magnetic resonance spectroscopy: a randomized single-blind crossover study

Intramyocellular acetylcarnitine (IMAC) is involved in exercise-related fuel metabolism. It is not known whether levels of systemic glucose influence IMAC levels in type 1 diabetes.

Molecular epidemiology reveals long-term changes in HIV type 1 subtype B transmission in Switzerland

Sequence data from resistance testing offer unique opportunities to characterize the structure of human immunodeficiency virus (HIV) infection epidemics.

Nerve excitability studies characterize Kv1.1 fast potassium channel dysfunction in patients with episodic ataxia type 1

Episodic ataxia type 1 is a neuronal channelopathy caused by mutations in the KCNA1 gene encoding the fast K(+) channel subunit K(v)1.1. Episodic ataxia type 1 presents with brief episodes of cerebellar dysfunction and persistent neuromyotonia and is associated with an increased incidence of epilepsy. In myelinated peripheral nerve, K(v)1.1 is highly expressed in the juxtaparanodal axon, where potassium channels limit the depolarizing afterpotential and the effects of depolarizing currents. Axonal excitability studies were performed on patients with genetically confirmed episodic ataxia type 1 to characterize the effects of K(v)1.1 dysfunction on motor axons in vivo. The median nerve was stimulated at the wrist and compound muscle action potentials were recorded from abductor pollicis brevis. Threshold tracking techniques were used to record strength-duration time constant, threshold electrotonus, current/threshold relationship and the recovery cycle. Recordings from 20 patients from eight kindreds with different KCNA1 point mutations were compared with those from 30 normal controls. All 20 patients had a history of episodic ataxia and 19 had neuromyotonia. All patients had similar, distinctive abnormalities: superexcitability was on average 100% higher in the patients than in controls (P < 0.00001) and, in threshold electrotonus, the increase in excitability due to a depolarizing current (20% of threshold) was 31% higher (P < 0.00001). Using these two parameters, the patients with episodic ataxia type 1 and controls could be clearly separated into two non-overlapping groups. Differences between the different KCNA1 mutations were not statistically significant. Studies of nerve excitability can identify K(v)1.1 dysfunction in patients with episodic ataxia type 1. The simple 15 min test may be useful in diagnosis, since it can differentiate patients with episodic ataxia type 1 from normal controls with high sensitivity and specificity.

Sensor-augmented pump therapy lowers HbA(1c) in suboptimally controlled Type?1 diabetes; a randomized controlled trial

To investigate the efficacy of sensor-augmented pump therapy vs. multiple daily injection therapy in patients with suboptimally controlled Type 1 diabetes.

SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients

SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

Macrocephaly in neurofibromatosis type 1: a sign post for optic pathway gliomas?

Optic pathway gliomas, which occur in 15-20% of paediatric patients with neurofibromatosis type 1, are the most common central nervous system tumour associated with this neurocutaneous disorder. The detection of optic pathway gliomas is essential for further management but is often delayed in infancy due to oligosymptomatic progression and difficulties in clinical detection. Therefore, the aim of our study was to find a clinical indicator for the presence of optic pathway gliomas in children with neurofibromatosis type 1 in order to facilitate early diagnosis and initiate further ophthalmological and neuroimaging investigations.

Influence of time point of calibration on accuracy of continuous glucose monitoring in individuals with type 1 diabetes

Abstract Background and Aims: Data on the influence of calibration on accuracy of continuous glucose monitoring (CGM) are scarce. The aim of the present study was to investigate whether the time point of calibration has an influence on sensor accuracy and whether this effect differs according to glycemic level. Subjects and Methods: Two CGM sensors were inserted simultaneously in the abdomen on either side of 20 individuals with type 1 diabetes. One sensor was calibrated predominantly using preprandial glucose (calibration(PRE)). The other sensor was calibrated predominantly using postprandial glucose (calibration(POST)). At minimum three additional glucose values per day were obtained for analysis of accuracy. Sensor readings were divided into four categories according to the glycemic range of the reference values (low, ≤4 mmol/L; euglycemic, 4.1-7 mmol/L; hyperglycemic I, 7.1-14 mmol/L; and hyperglycemic II, >14 mmol/L). Results: The overall mean±SEM absolute relative difference (MARD) between capillary reference values and sensor readings was 18.3±0.8% for calibration(PRE) and 21.9±1.2% for calibration(POST) (P<0.001). MARD according to glycemic range was 47.4±6.5% (low), 17.4±1.3% (euglycemic), 15.0±0.8% (hyperglycemic I), and 17.7±1.9% (hyperglycemic II) for calibration(PRE) and 67.5±9.5% (low), 24.2±1.8% (euglycemic), 15.5±0.9% (hyperglycemic I), and 15.3±1.9% (hyperglycemic II) for calibration(POST). In the low and euglycemic ranges MARD was significantly lower in calibration(PRE) compared with calibration(POST) (P=0.007 and P<0.001, respectively). Conclusions: Sensor calibration predominantly based on preprandial glucose resulted in a significantly higher overall sensor accuracy compared with a predominantly postprandial calibration. The difference was most pronounced in the hypo- and euglycemic reference range, whereas both calibration patterns were comparable in the hyperglycemic range.

An Actor-Critic based controller for glucose regulation in type 1 diabetes

A novel adaptive approach for glucose control in individuals with type 1 diabetes under sensor-augmented pump therapy is proposed. The controller, is based on Actor-Critic (AC) learning and is inspired by the principles of reinforcement learning and optimal control theory. The main characteristics of the proposed controller are (i) simultaneous adjustment of both the insulin basal rate and the bolus dose, (ii) initialization based on clinical procedures, and (iii) real-time personalization. The effectiveness of the proposed algorithm in terms of glycemic control has been investigated in silico in adults, adolescents and children under open-loop and closed-loop approaches, using announced meals with uncertainties in the order of ±25% in the estimation of carbohydrates. The results show that glucose regulation is efficient in all three groups of patients, even with uncertainties in the level of carbohydrates in the meal. The percentages in the A+B zones of the Control Variability Grid Analysis (CVGA) were 100% for adults, and 93% for both adolescents and children. The AC based controller seems to be a promising approach for the automatic adjustment of insulin infusion in order to improve glycemic control. After optimization of the algorithm, the controller will be tested in a clinical trial.

Real-time adaptive models for the personalized prediction of glycemic profile in type 1 diabetes patients

Prediction of glycemic profile is an important task for both early recognition of hypoglycemia and enhancement of the control algorithms for optimization of insulin infusion rate. Adaptive models for glucose prediction and recognition of hypoglycemia based on statistical and artificial intelligence techniques are presented.

2,3-Dichloro-1,4-hydroquinone 2,3-dichloro-1,4-benzoquinone monohydrate: a quinhydrone-type 1:1 donor-acceptor [D-A] charge-transfer complex

In the crystal structure of the title compound (systematic name: 2,3-dichlorobenzene-1,4-diol 2,3-dichlorocyclohexa-2,5-diene-1,4-dione monohydrate), C(6)H(4)Cl(2)O(2)center dot C(6)H(2)Cl(2)O(2)center dot H(2)O, the 2,3-dichloro-1,4-hydroquinone donor (D) and the 2,3-dichloro-1,4-benzoquinone acceptor (A) molecules form alternating stacks along [100]. Their molecular planes [maximum deviations for non-H atoms: 0.0133 (14) (D) and 0.0763 (14) angstrom (A)] are inclined to one another by 1.45 (3)degrees and are thus almost parallel. There are pi-pi interactions involving the D and A molecules, with centroid-centroid distances of 3.5043 (9) and 3.9548 (9) angstrom. Intermolecular O-H center dot center dot center dot O hydrogen bonds involving the water molecule and the hydroxy and ketone groups lead to the formation of two-dimensional networks lying parallel to (001). These networks are linked by C-H center dot center dot center dot O interactions, forming a three-dimensional structure.

Central and peripheral components of exercise-related fatigability in myotonic dystrophy type 1

Fatigue frequently occurs in myotonic dystrophy type 1 (DM1), but its pathophysiology remains unclear. This study assessed central and peripheral components of exercise-related fatigability in patients with DM1, compared to controls.