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Aim To develop a non-invasive hypoglycemia detection approach using smartwatch data. Research Design and Methods We prospectively collected data from two wrist-worn wearables (Garmin vivoactive 4S; Empatica E4) and continuous glucose monitoring values in adults with diabetes mellitus on insulin treatment. Using this data, we developed a machine learning (ML) approach to detect hypoglycemia ( Results Twenty-two individuals were included in the final analysis (age 54.5±15.2y, HbA1c 6.9±0.6%, 16 male). Hypoglycemia was detected with an area under the receiver operating characteristic curve of 0.76±0.07 solely based on wearable data. Feature analysis revealed that the ML model associated increased heart rate, decreased heart rate variability, and increased tonic electrodermal activity with hypoglycemia. Conclusions Our approach may allow for non-invasive hypoglycemia detection using wearables in people with diabetes and thus complement existing methods for hypoglycemia detection and warning.

Aim: To develop a non-invasive machine learning (ML) approach to detect hypoglycemia during real car driving based on driving (CAN) , and eye and head motion (EHM) data. Methods: We logged CAN and EHM data in 21 subjects with type 1 diabetes (18 male, 41 ± yrs, A1c 6.8 ± 0.7 % [51 ± 7 mmol/mol]) during driving in eu- (EU) and hypoglycemia (< 3.0 mmol/L, HYPO) . Participants drove in a car (Volkswagen Touran) supervised by a driving instructor on a closed test-track. Using CAN and EHM data, we built ML models to predict the probability of the driver being in HYPO. To make our approach applicable to different generations of cars, we present 3 ML models: first, a model combining CAN+EHM, representing the modern car with integrated camera. Second, a CAN model using driving data only, since modern cars are not generally equipped with EHM tracking. Third, anticipating that autonomous driving will limit the role of CAN data in the future, we tested a model solely based on EHM. Results: Mean BG in EU and HYPO was 6.3 ± 0.8 mmol/L and 2.5 ± 0.5 mmol/L (p< 0.001) , respectively. The model CAN+EHM achieved an area under the receiver operating characteristic curve of 0.88 ± 0.05, sensitivity of 0.70 ± 0.30, and specificity of 0.83 ± 0.in detecting HYPO. Further results are in Fig. 1. Conclusion: We propose ML-based approaches to non-invasively detect HYPO from driver behavior, applicable to contemporary cars and anticipating developments in automotive technology. Disclosure V.Lehmann: None. E.Fleisch: None. T.Kowatsch: Advisory Panel; Pathmate Technologies AG, Research Support; CSS Insurance, Stock/Shareholder; Pathmate Technologies AG. S.N.Lagger: None. M.Laimer: None. F.Wortmann: None. C.Stettler: None. T.Zueger: None. M.Maritsch: None. M.Notter: None. S.Schallmoser: None. C.Bérubé: None. C.Albrecht: None. M.Kraus: None. S.Feuerriegel: None. Funding Swiss National Science Foundation (SNF CRSII5_183569) , Swiss Diabetes Foundation, Diabetes Center Berne, Automobile Club Switzerland (ACS) , Federal Department of Defence, Civil Protection and Sport (DDPS) and Department of Research of the University Hospital Berne

Aim: To non-invasively detect hypoglycemia in individuals with type 1 diabetes (T1D) based on gaze behavior while driving. Methods: Controlled hypoglycemia was induced in 19 individuals (12 males, age 32 ± 7.1 yrs) with T1D (HbA1c 7.1 ± 0.6% [54 ± 6 mmol/mol]) using an adapted hypoglycemic clamp protocol. Gaze and blood glucose (BG) data were gathered while driving in a simulator during three 18 min sessions: session 1 (BG 90-144 mg/dL), session 2 (BG declining from 72 to 45 mg/dL), and session 3 (BG 36-45 mg/dL). A gradient-boosting machine learning (ML) model was built for hypoglycemia (BG Results: Mean venous BG was 105.4 ± 11.4 mg/dL during session 1, declined from 61.4 ± 6.1 mg/dL to 47.2 ± 8.5 mg/dL during session 2, and was 42.7 ± 4.1 mg/dL during session 3, respectively. Gaze analysis provided 29,968 data samples (1,577.5 ± 52 per subject, 10,041 euglycemia, 19,927 hypoglycemia). Overall, ML achieved an area under the receiver-operating-characteristics curve of 0.83 ± 0.09 for hypoglycemia detection with leave-one-subject-out cross-validation. Conclusion: ML-based gaze analysis shows high accuracy in non-invasive hypoglycemia detection while driving. Our approach offers promising potential in various settings where cameras are available. Disclosure V. Lehmann: None. E. Fleisch: Research Support; Self; CSS Health Insurance, Switzerland, Stock/Shareholder; Self; Pathmate-Technologies AG, Switzerland. F. Wortmann: None. C. Stettler: None. M. Maritsch: None. T. Zueger: None. A. Marxer: None. C. Berube: None. M. Kraus: None. C. Albrecht: None. S. Feuerriegel: None. T. Kowatsch: Advisory Panel; Self; Pathmate Technologies AG, Switzerland and Germany, Stock/Shareholder; Self; Pathmate Technologies AG, Switzerland and Germany. Funding Swiss National Science Foundation (SNF CRSII5_183569); Insel Group; Diabetes Center Berne

Patient-specific rehearsal (PsR) is a new concept whereby a procedure can be rehearsed virtually using the exact patient’s anatomical data prior to performing the real procedure. The aim of this study was to ascertain if endovascular virtual-reality PsR simulation enhanced performance in real life. This was done by performing a systematic review following the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines. A literature search was conducted in PubMed, Embase, The Cochrane Library and Web of Science concerning PsR in endovascular procedures. All publications were handled using Covidence. Reference lists were also screened. Data extracted from the studies were realism rating, procedure time, fluoroscopy time, contrast volume, number of angiograms and reduction of errors. Kirkpatrick’s four-level model for measuring the efficiency of training was used for guidance of the relevance of studies. The search yielded 1155 results after the exclusion of duplicates, and 11 studies were included. Four studies had a control group, including one randomized trial; the remaining seven were feasibility studies. The realism was rated high, and overall, the studies showed improvements in procedure time, fluoroscopy time and contrast volume after PsR. One study assessed and confirmed the reduction in errors after PsR. Only two studies included more than 15 patients in their cohort. Kirkpatrick’s model was applied to all studies, with one study reaching level 4. All studies found the concept of PsR to be feasible and realistic. The studies with a control group showed a reduction of overall procedure time, radiation exposure and potential errors in endovascular procedures following PsR.

Wastewater production in a hospital laundry and the treatment of the most critical wastewater stream, are assessed. Hospital laundry wastewaters are hazardous to the environment due to their high pollutant concentrations and the chemicals added during the clothes washing process. Heterogeneous photocatalysis with UV, O 3 and TiO 2 and their possible combinations were used for disinfection purposes. A ramp-type reactor was used for TiO 2 (P25 Degussa) fixation and for photochemical diffusion of the ozonized air. After assessing 5-day biological oxygen demand, chemical oxygen demand, pH, turbidity, and surfactant content, and checking for the presence of thermotolerant coliforms and Escherichia coli, it was concluded that UV/O 3 /TiO 2 was the best process/combination, yielding a 100% disinfection rate and a microbiological inactivation of 0.5070 min -1 for E. coli and of 0.5505 min -1 for thermotolerant coliforms.

OBJECTIVE This study examined the effects of ACTH 4-10, a fragment of adrenocorticotropin (ACTH) with known central nervous system (CNS) activity, on the dimensional complexity of the ongoing electroencephalographic (EEG) activity. Stressful stimuli cause ACTH to be released from the pituitary, and as a neuropeptide ACTH may concurrently exert adaptive influences on the brain's processing of these stimuli. Previous studies have indicated an impairing influence of ACTH on selective attention. METHODS Dimensional complexity of the EEG, which indexes the brain's way of stimulus processing, was evaluated while subjects performed tasks with different attention demands. Sixteen healthy men (23 to 33 years) were tested once after placebo and another time after administration of ACTH 4-10 (1.25 mg intravenously (i.v.), 30 minutes before testing). The EEG was recorded while subjects were presented with a dichotic listening task (consisting of the concurrent presentation of tone pips to the left and right ear). Subjects either a) listened to pips in both ears (divided attention), or b) listened selectively to pips in one ear (selective attention), or c) ignored all pips. RESULTS Dimensional complexity of the EEG was higher during divided than selective attention. ACTH significantly increased the EEG complexity during selective attention, in particular over the midfrontal cortex (Fz, Cz). CONCLUSIONS The effects support the view of a de-focusing action of ACTH during selective attention that could serve to improve the organism's adaptation to stress stimuli.

Polymorphisms of interleukin-1 beta gene (IL1B-511CT) are considered as risk factor for gastric carcinogenesis, but conflicting data have been reported recently.The distribution of the four major IL1B variants (IL1B-3737CT, -1464GC, - 511CT, -31TC) were analyzed in 116 and 142 patients with gastric cancer and 'high risk gastritis', respectively, as well as 94 healthy controls.While identified frequencies of genotypes, haplotypes and haplotype pairs corresponded to those of other studies in Caucasians, none were significantly associated with the presence of gastric cancer or premalignant alterations.None of the four major polymorphisms is individually or in its haplotype configuration linked to the development of GC in this Caucasian population in Germany.