Safety and Feasibility of a Diagnostic Algorithm Combining Clinical Probability, d-Dimer Testing, and Ultrasonography for Suspected Upper Extremity Deep Venous Thrombosis: A Prospective Management Study.

BACKGROUND Although well-established for suspected lower limb deep venous thrombosis, an algorithm combining a clinical decision score, d-dimer testing, and ultrasonography has not been evaluated for suspected upper extremity deep venous thrombosis (UEDVT). OBJECTIVE To assess the safety and feasibility of a new diagnostic algorithm in patients with clinically suspected UEDVT. DESIGN Diagnostic management study. (ClinicalTrials.gov: NCT01324037) SETTING: 16 hospitals in Europe and the United States. PATIENTS 406 inpatients and outpatients with suspected UEDVT. MEASUREMENTS The algorithm consisted of the sequential application of a clinical decision score, d-dimer testing, and ultrasonography. Patients were first categorized as likely or unlikely to have UEDVT; in those with an unlikely score and normal d-dimer levels, UEDVT was excluded. All other patients had (repeated) compression ultrasonography. The primary outcome was the 3-month incidence of symptomatic UEDVT and pulmonary embolism in patients with a normal diagnostic work-up. RESULTS The algorithm was feasible and completed in 390 of the 406 patients (96%). In 87 patients (21%), an unlikely score combined with normal d-dimer levels excluded UEDVT. Superficial venous thrombosis and UEDVT were diagnosed in 54 (13%) and 103 (25%) patients, respectively. All 249 patients with a normal diagnostic work-up, including those with protocol violations (n = 16), were followed for 3 months. One patient developed UEDVT during follow-up, for an overall failure rate of 0.4% (95% CI, 0.0% to 2.2%). LIMITATIONS This study was not powered to show the safety of the substrategies. d-Dimer testing was done locally. CONCLUSION The combination of a clinical decision score, d-dimer testing, and ultrasonography can safely and effectively exclude UEDVT. If confirmed by other studies, this algorithm has potential as a standard approach to suspected UEDVT. PRIMARY FUNDING SOURCE None.

The role of phospholipase D in modulating the MTOR signaling pathway in polycystic kidney disease

The mammalian target of rapamycin (mTOR) signaling pathway is aberrantly activated in polycystic kidney disease (PKD). Emerging evidence suggests that phospholipase D (PLD) and its product phosphatidic acid (PA) regulate mTOR activity. In this study, we assessed in vitro the regulatory function of PLD and PA on the mTOR signaling pathway in PKD. We found that the basal level of PLD activity was elevated in PKD cells. Targeting PLD by small molecule inhibitors reduced cell proliferation and blocked mTOR signaling, whereas exogenous PA stimulated mTOR signaling and abolished the inhibitory effect of PLD on PKD cell proliferation. We also show that blocking PLD activity enhanced the sensitivity of PKD cells to rapamycin and that combining PLD inhibitors and rapamycin synergistically inhibited PKD cell proliferation. Furthermore, we demonstrate that targeting mTOR did not induce autophagy, whereas targeting PLD induced autophagosome formation. Taken together, our findings suggest that deregulated mTOR pathway activation is mediated partly by increased PLD signaling in PKD cells. Targeting PLD isoforms with pharmacological inhibitors may represent a new therapeutic strategy in PKD.

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm.

The ethanolic fermentation pathway supports respiration and lipid biosynthesis in tobacco pollen

Rapid pollen tube growth requires a high rate of sugar metabolism to meet energetic and biosynthetic demands. Previous work on pollen sugar metabolism showed that tobacco pollen carry out efficient ethanolic fermentation concomitantly with a high rate of respiration (Bucher et al ., 1995). Here we show that the products of fermentation, acetaldehyde and ethanol, are further metabolised in a pathway that bypasses mitochondrial PDH. The enzymes involved in this pathway are pyruvate decarboxylase, aldehyde dehydrogenase and acetyl-CoA synthetase. Radiolabelling experiments show that during tobacco pollen tube growth label of C-14-ethanol is incorporated into CO2 as well as into lipids and other higher molecular weight compounds. A role for the glyoxylate cycle appears unlikely since activity of malate synthase, a key enzyme of the glyoxylate cycle, could not be detected.

Management of postpartum hemorrhage (PPH): algorithm of the interdisciplinary D-A-CH consensus group PPH (Germany – Austria – Switzerland)

Postpartum hemorrhage (PPH) is one of the main causes of maternal deaths even in industrialized countries. It represents an emergency situation which necessitates a rapid decision and in particular an exact diagnosis and root cause analysis in order to initiate the correct therapeutic measures in an interdisciplinary cooperation. In addition to established guidelines, the benefits of standardized therapy algorithms have been demonstrated. A therapy algorithm for the obstetric emergency of postpartum hemorrhage in the German language is not yet available. The establishment of an international (Germany, Austria and Switzerland D-A-CH) "treatment algorithm for postpartum hemorrhage" was an interdisciplinary project based on the guidelines of the corresponding specialist societies (anesthesia and intensive care medicine and obstetrics) in the three countries as well as comparable international algorithms for therapy of PPH.The obstetrics and anesthesiology personnel must possess sufficient expertise for emergency situations despite lower case numbers. The rarity of occurrence for individual patients and the life-threatening situation necessitate a structured approach according to predetermined treatment algorithms. This can then be carried out according to the established algorithm. Furthermore, this algorithm presents the opportunity to train for emergency situations in an interdisciplinary team.

Driving and dementia: a clinical decision pathway

OBJECTIVE This study aimed to develop a pathway to bring together current UK legislation, good clinical practice and appropriate management strategies that could be applied across a range of healthcare settings. METHODS The pathway was constructed by a multidisciplinary clinical team based in a busy Memory Assessment Service. A process of successive iteration was used to develop the pathway, with input and refinement provided via survey and small group meetings with individuals from a wide range of regional clinical networks and diverse clinical backgrounds as well as discussion with mobility centres and Forum of Mobility Centres, UK. RESULTS We present a succinct clinical pathway for patients with dementia, which provides a decision-making framework for how health professionals across a range of disciplines deal with patients with dementia who drive. CONCLUSIONS By integrating the latest guidance from diverse roles within older people's health services and key experts in the field, the resulting pathway reflects up-to-date policy and encompasses differing perspectives and good practice. It is potentially a generalisable pathway that can be easily adaptable for use internationally, by replacing UK legislation for local regulations. A limitation of this pathway is that it does not address the concern of mild cognitive impairment and how this condition relates to driving safety. © 2014 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons, Ltd.

Improved Localization of Implanted Subdural Electrode Contacts on MRI Using an Elastic Image Fusion Algorithm in Invasive EEG Recording

BACKGROUND: Accurate projection of implanted subdural electrode contacts in presurgical evaluation of pharmacoresistant epilepsy cases by invasive EEG is highly relevant. Linear fusion of CT and MRI images may display the contacts in the wrong position due to brain shift effects. OBJECTIVE: A retrospective study in five patients with pharmacoresistant epilepsy was performed to evaluate whether an elastic image fusion algorithm can provide a more accurate projection of the electrode contacts on the pre-implantation MRI as compared to linear fusion. METHODS: An automated elastic image fusion algorithm (AEF), a guided elastic image fusion algorithm (GEF), and a standard linear fusion algorithm (LF) were used on preoperative MRI and post-implantation CT scans. Vertical correction of virtual contact positions, total virtual contact shift, corrections of midline shift and brain shifts due to pneumencephalus were measured. RESULTS: Both AEF and GEF worked well with all 5 cases. An average midline shift of 1.7mm (SD 1.25) was corrected to 0.4mm (SD 0.8) after AEF and to 0.0mm (SD 0) after GEF. Median virtual distances between contacts and cortical surface were corrected by a significant amount, from 2.3mm after LF to 0.0mm after AEF and GEF (p<.001). Mean total relative corrections of 3.1 mm (SD 1.85) after AEF and 3.0mm (SD 1.77) after GEF were achieved. The tested version of GEF did not achieve a satisfying virtual correction of pneumencephalus. CONCLUSION: The technique provided a clear improvement in fusion of pre- and post-implantation scans, although the accuracy is difficult to evaluate.

The Host Nonsense-Mediated mRNA Decay Pathway Restricts Mammalian RNA Virus Replication

In addition to classically defined immune mechanisms, cell-intrinsic processes can restrict virus infection and have shaped virus evolution. The details of this virus-host interaction are still emerging. Following a genome-wide siRNA screen for host factors affecting replication of Semliki Forest virus (SFV), a positive-strand RNA (+RNA) virus, we found that depletion of nonsense-mediated mRNA decay (NMD) pathway components Upf1, Smg5, and Smg7 led to increased levels of viral proteins and RNA and higher titers of released virus. The inhibitory effect of NMD was stronger when virus replication efficiency was impaired by mutations or deletions in the replicase proteins. Consequently, depletion of NMD components resulted in a more than 20-fold increase in production of these attenuated viruses. These findings indicate that a cellular mRNA quality control mechanism serves as an intrinsic barrier to the translation of early viral proteins and the amplification of +RNA viruses in animal cells.

A framework for benchmarking of homogenisation algorithm performance on the global scale

The International Surface Temperature Initiative (ISTI) is striving towards substantively improving our ability to robustly understand historical land surface air temperature change at all scales. A key recently completed first step has been collating all available records into a comprehensive open access, traceable and version-controlled databank. The crucial next step is to maximise the value of the collated data through a robust international framework of benchmarking and assessment for product intercomparison and uncertainty estimation. We focus on uncertainties arising from the presence of inhomogeneities in monthly mean land surface temperature data and the varied methodological choices made by various groups in building homogeneous temperature products. The central facet of the benchmarking process is the creation of global-scale synthetic analogues to the real-world database where both the "true" series and inhomogeneities are known (a luxury the real-world data do not afford us). Hence, algorithmic strengths and weaknesses can be meaningfully quantified and conditional inferences made about the real-world climate system. Here we discuss the necessary framework for developing an international homogenisation benchmarking system on the global scale for monthly mean temperatures. The value of this framework is critically dependent upon the number of groups taking part and so we strongly advocate involvement in the benchmarking exercise from as many data analyst groups as possible to make the best use of this substantial effort.

Diagnosis and management of filler adverse effects: an algorithm.

Fillers are frequently used in beautifying procedures. Despite major advancements of the chemical and biological features of injected materials, filler-related adverse events may occur, and can substantially impact the clinical outcome. Filler granulomas become manifest as visible grains, nodules, or papules around the site of the primary injection. Early recognition and proper treatment of filler-related complications is important because effective treatment options are available. In this report, we provide a comprehensive overview of the differential diagnosis and diagnostics and develop an algorithm of successful therapy regimens.