Time of emergence of trends in ocean biogeochemistry

For the detection of climate change, not only the magnitude of a trend signal is of significance. An essential issue is the time period required by the trend to be detectable in the first place. An illustrative measure for this is time of emergence (ToE), that is, the point in time when a signal finally emerges from the background noise of natural variability. We investigate the ToE of trend signals in different biogeochemical and physical surface variables utilizing a multi-model ensemble comprising simulations of 17 Earth system models (ESMs). We find that signals in ocean biogeochemical variables emerge on much shorter timescales than the physical variable sea surface temperature (SST). The ToE patterns of pCO2 and pH are spatially very similar to DIC (dissolved inorganic carbon), yet the trends emerge much faster – after roughly 12 yr for the majority of the global ocean area, compared to between 10 and 30 yr for DIC. ToE of 45–90 yr are even larger for SST. In general, the background noise is of higher importance in determining ToE than the strength of the trend signal. In areas with high natural variability, even strong trends both in the physical climate and carbon cycle system are masked by variability over decadal timescales. In contrast to the trend, natural variability is affected by the seasonal cycle. This has important implications for observations, since it implies that intra-annual variability could question the representativeness of irregularly sampled seasonal measurements for the entire year and, thus, the interpretation of observed trends.

A climatological analysis of high-precipitation events in Dronning Maud Land, Antarctica, and associated large-scale atmospheric conditions

The link between high precipitation in Dronning Maud Land (DML), Antarctica, and the large-scale atmospheric circulation is investigated using ERA-Interim data for 1979–2009. High-precipitation events are analyzed at Halvfarryggen situated in the coastal region of DML and at Kohnen Station located in its interior. This study further includes a comprehensive comparison of high precipitation in ERA-Interim with precipitation data from the Antarctic Mesoscale Prediction System (AMPS) and snow accumulation measurements from automatic weather stations (AWSs), with the limitations of such a comparison being discussed. The ERA-Interim and AMPS precipitation data agree very well. However, the correspondence between high precipitation in ERA-Interim and high snow accumulation at the AWSs is relatively weak. High-precipitation events at both Halvfarryggen and Kohnen are typically associated with amplified upper level waves. This large-scale atmospheric flow pattern is preceded by the downstream development of a Rossby wave train from the eastern South Pacific several days before the precipitation event. At the surface, a cyclone located over the Weddell Sea is the main synoptic ingredient for high precipitation both at Halvfarryggen and at Kohnen. A blocking anticyclone downstream is not a requirement for high precipitation per se, but a larger share of blocking occurrences during the highest-precipitation days in DML suggests that these blocks strengthen the vertically integrated water vapor transport (IVT) into DML. A strong link between high precipitation and the IVT perpendicular to the local orography suggests that IVT could be used as a “proxy” for high precipitation, in particular over DML's interior.

Impact of miR-21, miR-126 and miR-221 as prognostic factors of clear cell renal cell carcinoma with tumor thrombus of the inferior vena cava

Clear cell renal cell carcinoma (ccRCC) characterized by a tumor thrombus (TT) extending into the inferior vena cava (IVC) generally indicates poor prognosis. Nevertheless, the risk for tumor recurrence after nephrectomy and thrombectomy varies. An applicable and accurate prediction system to select ccRCC patients with TT of the IVC (ccRCC/TT) at high risk after nephrectomy is urgently needed, but has not been established up to now. To our knowledge, a possible role of microRNAs (miRs) for the development of ccRCC/TT or their impact as prognostic markers in ccRCC/TT has not been explored yet. Therefore, we analyzed the expression of the previously described onco-miRs miR-200c, miR-210, miR-126, miR-221, let-7b, miR-21, miR-143 and miR-141 in a study collective of 74 ccRCC patients. Using the expression profiles of these eight miRs we developed classification systems that accurately differentiate ccRCC from non-cancerous renal tissue and ccRCC/TT from tumors without TT. In the subgroup of 37 ccRCC/TT cases we found that miR-21, miR-126, and miR-221 predicted cancer related death (CRD) accurately and independently from other clinico-pathological features. Furthermore, a combined risk score based on the expression of miR-21, miR-126 and miR-221 was developed and showed high sensitivity and specificity to predict cancer specific survival (CSS) in ccRCC/TT. Using the combined risk score we were able to classify ccRCC/TT patients correctly into high and low risk cases. The risk stratification by the combined risk score (CRS) will benefit from further cohort validation and might have potential for clinical application as a molecular prediction system to identify high- risk ccRCC/TT patients.

Guidelines for WB3 Part III: Stakeholder workshop 2: Selection and decision on prevention and mitigation strategies to be implemented

These guidelines were developed in the context of working block 3 of the DESIRE project. They address the facilitators in the 18 DESIRE study sites and support them in conducting stakeholder workshops aiming at the selection and decision on mitigation strategies to be implemented in the study site context. The decision-making process is supported by a multi-objective decision support system (MODSS) Software called 'Facilitator'.

Multi-Model Data Fusion to Improve an Early Warning System for Hypo-/Hyperglycemic Events

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

Transient Earth system responses to cumulative carbon dioxide emissions: linearities, uncertainties, and probabilities in an observation-constrained model ensemble

Information on the relationship between cumulative fossil CO2 emissions and multiple climate targets is essential to design emission mitigation and climate adaptation strategies. In this study, the transient response of a climate or environmental variable per trillion tonnes of CO2 emissions, termed TRE, is quantified for a set of impact-relevant climate variables and from a large set of multi-forcing scenarios extended to year 2300 towards stabilization. An  ∼ 1000-member ensemble of the Bern3D-LPJ carbon–climate model is applied and model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte Carlo-type framework. Uncertainties in TRE estimates include both scenario uncertainty and model response uncertainty. Cumulative fossil emissions of 1000 Gt C result in a global mean surface air temperature change of 1.9 °C (68 % confidence interval (c.i.): 1.3 to 2.7 °C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and a steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic meridional overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The constrained model ensemble is also applied to determine the response to a pulse-like emission and in idealized CO2-only simulations. The transient climate response is constrained, primarily by long-term ocean heat observations, to 1.7 °C (68 % c.i.: 1.3 to 2.2 °C) and the equilibrium climate sensitivity to 2.9 °C (2.0 to 4.2 °C). This is consistent with results by CMIP5 models but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability.

Virtobot--a multi-functional robotic system for 3D surface scanning and automatic post mortem biopsy

The Virtopsy project, a multi-disciplinary project that involves forensic science, diagnostic imaging, computer science, automation technology, telematics and biomechanics, aims to develop new techniques to improve the outcome of forensic investigations. This paper presents a new approach in the field of minimally invasive virtual autopsy for a versatile robotic system that is able to perform three-dimensional (3D) surface scans as well as post mortem image-guided soft tissue biopsies.

Detection and identification of 700 drugs by multi-target screening with a 3200 Q TRAP LC-MS/MS system and library searching

The multi-target screening method described in this work allows the simultaneous detection and identification of 700 drugs and metabolites in biological fluids using a hybrid triple-quadrupole linear ion trap mass spectrometer in a single analytical run. After standardization of the method, the retention times of 700 compounds were determined and transitions for each compound were selected by a "scheduled" survey MRM scan, followed by an information-dependent acquisition using the sensitive enhanced product ion scan of a Q TRAP hybrid instrument. The identification of the compounds in the samples analyzed was accomplished by searching the tandem mass spectrometry (MS/MS) spectra against the library we developed, which contains electrospray ionization-MS/MS spectra of over 1,250 compounds. The multi-target screening method together with the library was included in a software program for routine screening and quantitation to achieve automated acquisition and library searching. With the help of this software application, the time for evaluation and interpretation of the results could be drastically reduced. This new multi-target screening method has been successfully applied for the analysis of postmortem and traffic offense samples as well as proficiency testing, and complements screening with immunoassays, gas chromatography-mass spectrometry, and liquid chromatography-diode-array detection. Other possible applications are analysis in clinical toxicology (for intoxication cases), in psychiatry (antidepressants and other psychoactive drugs), and in forensic toxicology (drugs and driving, workplace drug testing, oral fluid analysis, drug-facilitated sexual assault).

An early warning system for hypoglycemic/hyperglycemic events based on fusion of adaptive prediction models

Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia/hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy.

An implantable carotid sinus baroreflex activating system: surgical technique and short-term outcome from a multi-center feasibility trial for the treatment of resistant hypertension

OBJECTIVES: To assess perioperative outcomes and blood pressure (BP) responses to an implantable carotid sinus baroreflex activating system being investigated for the treatment of resistant hypertension. METHODS: We report on the first seventeen patients enrolled in a multicenter study. Bilateral perivascular carotid sinus electrodes (CSL) and a pulse generator (IPG) are permanently implanted. Optimal placement of the CSL is determined by intraoperative BP responses to test activations. Acute BP responses were tested postoperatively and during the first four months of follow-up. RESULTS: Prior to implant, BP was 189.6+/-27.5/110.7+/-15.3 mmHg despite stable therapy (5.2+/-1.8 antihypertensive drugs). The mean procedure time was 202+/-43 minutes. No perioperative strokes or deaths occurred. System tests performed 1 or up to 3 days postoperatively resulted in significant (all p < or = 0.0001) mean maximum reduction, with standard deviations and 95% confidence limits for systolic BP, diastolic BP and heart rate of 28+/-22 (17, 39) mmHg, 16+/-11 (10, 22) mmHg and 8+/-4 (6, 11) BPM, respectively. Repeated testing during 3 months of therapeutic electrical activation demonstrated a durable response. CONCLUSIONS: These preliminary data suggest an acceptable safety of the procedure with a low rate of adverse events and support further clinical development of baroreflex activation as a new concept to treat resistant hypertension.