Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient’s data using two different strategies to control nocturnal and postprandial periods. Research Design and Methods: We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min. Results: Time spent in normoglycemia (BG, 3.9–8.0 mmol/L) during the nocturnal period (12 a.m.–8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3–75%) with OL to 95.8% (73–100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0–21%) in the OL night to 0.0% (0.0–0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9–10.0 mmol/L) 58.3% (29.1–87.5%) versus 50.0% (50–100%). Conclusions: A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia

Exploring polysilicon deposition conditions through a laboratory CVD prototype

Cost and energy consumption related to obtaining polysilicon impact significantly on the total photovoltaic module cost and its energy payback time. Process simplifications can be performed, leading to cost reductions. Nowadays, among several approaches currently pursued to produce the so called Solar Grade Silicon, the chemical route, named Siemens process, is the dominant one. At the Instituto de Energía Solar research on this topic is focused on the chemical route, in particular on the polysilicon deposition step by chemical vapor deposition (CVD) from Trichlorosilane through a laboratory prototype. Valuable information about the phenomena involved in the polysilicon deposition process and the operating conditions is obtained from our experiments. A particular feature of our system is the inclusion of a mass spectrometer. The present work comprises spectra characterization of the polysilicon deposition chemical reaction, temperature and inlet gas mixture composition influence on the deposition rate and analysis of polysilicon deposition conditions for the ?pop-corn' phenomenon to appear, based on experimental experience (Actas de la Special Issue: E-MRS 2012 Spring Meeting ? Symposium A

A machine learning approach to identify clinical trials involving nanodrugs and nanodevices from ClinicalTrials.gov

BACKGROUND: Clinical Trials (CTs) are essential for bridging the gap between experimental research on new drugs and their clinical application. Just like CTs for traditional drugs and biologics have helped accelerate the translation of biomedical findings into medical practice, CTs for nanodrugs and nanodevices could advance novel nanomaterials as agents for diagnosis and therapy. Although there is publicly available information about nanomedicine-related CTs, the online archiving of this information is carried out without adhering to criteria that discriminate between studies involving nanomaterials or nanotechnology-based processes (nano), and CTs that do not involve nanotechnology (non-nano). Finding out whether nanodrugs and nanodevices were involved in a study from CT summaries alone is a challenging task. At the time of writing, CTs archived in the well-known online registry ClinicalTrials.gov are not easily told apart as to whether they are nano or non-nano CTs-even when performed by domain experts, due to the lack of both a common definition for nanotechnology and of standards for reporting nanomedical experiments and results. METHODS: We propose a supervised learning approach for classifying CT summaries from ClinicalTrials.gov according to whether they fall into the nano or the non-nano categories. Our method involves several stages: i) extraction and manual annotation of CTs as nano vs. non-nano, ii) pre-processing and automatic classification, and iii) performance evaluation using several state-of-the-art classifiers under different transformations of the original dataset. RESULTS AND CONCLUSIONS: The performance of the best automated classifier closely matches that of experts (AUC over 0.95), suggesting that it is feasible to automatically detect the presence of nanotechnology products in CT summaries with a high degree of accuracy. This can significantly speed up the process of finding whether reports on ClinicalTrials.gov might be relevant to a particular nanoparticle or nanodevice, which is essential to discover any precedents for nanotoxicity events or advantages for targeted drug therapy.

Outward Rectification of Voltage-Gated K+ Channels Evolved at Least Twice in Life History

Voltage-gated potassium (K+) channels are present in all living systems. Despite high structural similarities in the transmembrane domains (TMD), this K+ channel type segregates into at least two main functional categories—hyperpolarization-activated, inward-rectifying (Kin) and depolarization-activated, outward-rectifying (Kout) channels. Voltage-gated K+ channels sense the membrane voltage via a voltage-sensing domain that is connected to the conduction pathway of the channel. It has been shown that the voltage-sensing mechanism is the same in Kin and Kout channels, but its performance results in opposite pore conformations. It is not known how the different coupling of voltage-sensor and pore is implemented. Here, we studied sequence and structural data of voltage-gated K+ channels from animals and plants with emphasis on the property of opposite rectification. We identified structural hotspots that alone allow already the distinction between Kin and Kout channels. Among them is a loop between TMD S5 and the pore that is very short in animal Kout, longer in plant and animal Kin and the longest in plant Kout channels. In combination with further structural and phylogenetic analyses this finding suggests that outward-rectification evolved twice and independently in the animal and plant kingdom.