Outcomes of High-Frequency Gastric Electric Stimulation for the Treatment of Severe, Medically Refractory Gastroparesis in Finland

Background and Aims: Severe, medically uncontrollable gastroparesis is a rare entity, which can be treated using a high-frequency gastric electric stimulator implanted surgically. Previous follow-ups have proven positive outcomes with gastric electric stimulator in patients with gastroparesis. The aim of this study was to evaluate the efficacy and safety of gastric electric stimulator in patients, in whom gastroparesis could not be controlled by conservative means in our country. Materials and Methods: This is a retrospective multi-center cohort comprising all patients who had been implanted gastric electric stimulator for severe, medically refractory gastroparesis during 2007-2015 in Finland. Results: Fourteen patients underwent implantation of gastric electrical stimulator without any postoperative complications. Laparoscopic approach was used in 13 patients (93%). Prior implantation, all patients needed frequent hospitalization for parenteral feeding, 13 had severe nausea, 11 had severe vomiting, 10 had notable weight loss, and 6 had frequent abdominal pain. After operation, none of the patients required parenteral feeding, 11 patients (79%) gained median of 5.1 kg in weight (P <0.01), and symptoms were relieved markedly in 8 and partially in 3 patients (79%). Of partial responders, two continued to experience occasional vomiting and one mild nausea. Five patients needed medication for gastroparesis after the operation. One patient did not get any relief of symptoms, but gained 6 kg in weight. No major late complications occurred. Conclusion: Gastric electrical stimulator seems to improve the nutritional status and give clear relief of the symptoms of severe, medically uncontrollable gastroparesis. Given the low number of operations, gastric electrical stimulator seems to be underused in Finland.Peer reviewe

Erythropoietin (EPO) increases myelin gene expression in CG4 oligodendrocyte cells through the classical EPO receptor

Erythropoietin (EPO) has protective effects in neurodegenerative and neuroinflammatory diseases, including in animal models of multiple sclerosis, where EPO decreases disease severity. EPO also promotes neurogenesis and is protective in models of toxic demyelination. In this study, we asked whether EPO could promote neurorepair by also inducing remyelination. In addition, we investigated whether the effect of EPO could be mediated by the classical erythropoietic EPO receptor (EPOR), since it is still questioned if EPOR is functional in non-hematopoietic cells. Using CG4 cells, a line of rat oligodendrocyte precursor cells, we found that EPO increases the expression of myelin genes (myelin oligodendrocyte glycoprotein (MOG) and myelin basic protein (MBP)). EPO had no effect in wild-type CG4 cells, which do not express EPOR, whereas it increased MOG and MBP expression in cells engineered to overexpress EPOR (CG4-EPOR). This was reflected in a marked increase in MOG protein levels, as detected by western blot. In these cells, EPO induced by 10-fold the early growth response gene 2 (Egr2), which is required for peripheral myelination. However, Egr2 silencing with a siRNA did not reverse the effect of EPO, indicating that EPO acts through other pathways. In conclusion, EPO induces the expression of myelin genes in oligodendrocytes and this effect requires the presence of EPOR. This study demonstrates that EPOR can mediate neuroreparative effects

Biomarkers and prediction of myocardial triglyceride content in non-diabetic men

Background and aims: Lipid oversupply to cardiomyocytes or decreased utilization of lipids leads to cardiac steatosis. We aimed to examine the role of different circulating metabolic biomarkers as predictors of myocardial triglyceride (TG) content in non-diabetic men. Methods and results: Myocardial and hepatic TG contents were measured with 1.5 T magnetic resonance (MR) spectroscopy, and LV function, visceral adipose tissue (VAT), abdominal subcutaneous tissue (SAT), epicardial and pericardial fat by MR imaging in 76 non-diabetic men. Serum concentration of circulating metabolic biomarkers [adiponectin, leptin, adipocyte-fatty acid binding protein 4 (A-FABP 4), resistin, and lipocalin-2] including beta-hydroxybuturate (beta-OHB) were measured. Subjects were stratified by tertiles of myocardial TG into low, moderate, and high myocardial TG content groups. Concentrations of beta-OHB were lower (p = 0.003) and serum levels of A-FABP 4 were higher (p <0.001) in the group with high myocardial TG content compared with the group with low myocardial TG content. beta-OHB was negatively correlated with myocardial TG content (r = -0.316, p = 0.006), whereas A-FABP 4 was not correlated with myocardial TG content (r = 0.192, p = 0.103). In multivariable analyses beta-OHB and plasma glucose levels were the best predictors of myocardial TG content independently of VAT and hepatic TG content. The model explained 58.8% of the variance in myocardial TG content. Conclusion: Our data showed that beta-OHB and fasting glucose were the best predictors of myocardial TG content in non-diabetic men. These data suggest that hyperglycemia and alterations in lipid oxidation may be associated with cardiac steatosis in humans. (C) 2015 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.Peer reviewe

The role of zinc in the anti-tumour and anti-cachectic activity of D-myo-inositol 1,2,6-triphosphate

Background: D-myo-inositol-1,2,6-triphosphate (a-trinositol, AT) is a polyanionic molecule capable of chelating divalent metal ions with anti-tumour and anti-cachectic activity in a murine model. Methods: To investigate the role of zinc in this process, mice bearing cachexia-inducing MAC16 tumour were treated with AT, with or without concomitant administration of ZnSO4. Results: At a dose of 40mgkg-1, AT effectively attenuated both weight loss and growth of the MAC16 tumour, and both effects were attenuated by co-administration of Zn2+. The concentration of zinc in gastrocnemius muscle increased with increasing weight loss, whereas administration of AT decreased the levels of zinc in plasma, skeletal muscle and tumour, which were restored back to control values after administration of ZnSO4. Conclusion: These results suggest that zinc is important in both tumour growth and cachexia in this animal model

The genotype-phenotype relationship in multicellular pattern-generating models - the neglected role of pattern descriptors

Background: A deep understanding of what causes the phenotypic variation arising from biological patterning processes, cannot be claimed before we are able to recreate this variation by mathematical models capable of generating genotype-phenotype maps in a causally cohesive way. However, the concept of pattern in a multicellular context implies that what matters is not the state of every single cell, but certain emergent qualities of the total cell aggregate. Thus, in order to set up a genotype-phenotype map in such a spatiotemporal pattern setting one is actually forced to establish new pattern descriptors and derive their relations to parameters of the original model. A pattern descriptor is a variable that describes and quantifies a certain qualitative feature of the pattern, for example the degree to which certain macroscopic structures are present. There is today no general procedure for how to relate a set of patterns and their characteristic features to the functional relationships, parameter values and initial values of an original pattern-generating model. Here we present a new, generic approach for explorative analysis of complex patterning models which focuses on the essential pattern features and their relations to the model parameters. The approach is illustrated on an existing model for Delta-Notch lateral inhibition over a two-dimensional lattice. Results: By combining computer simulations according to a succession of statistical experimental designs, computer graphics, automatic image analysis, human sensory descriptive analysis and multivariate data modelling, we derive a pattern descriptor model of those macroscopic, emergent aspects of the patterns that we consider of interest. The pattern descriptor model relates the values of the new, dedicated pattern descriptors to the parameter values of the original model, for example by predicting the parameter values leading to particular patterns, and provides insights that would have been hard to obtain by traditional methods. Conclusion: The results suggest that our approach may qualify as a general procedure for how to discover and relate relevant features and characteristics of emergent patterns to the functional relationships, parameter values and initial values of an underlying pattern-generating mathematical model

Bacterial communities in penile skin, male urethra, and vaginas of heterosexual couples with and without bacterial vaginosis

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Microbiome 4 (2016): 16, doi:10.1186/s40168-016-0161-6.The epidemiology of bacterial vaginosis (BV) suggests it is sexually transmissible, yet no transmissible agent has been identified. It is probable that BV-associated bacterial communities are transferred from male to female partners during intercourse; however, the microbiota of sexual partners has not been well-studied. Pyrosequencing analysis of PCR-amplified 16S rDNA was used to examine BV-associated bacteria in monogamous couples with and without BV using vaginal, male urethral, and penile skin specimens. The penile skin and urethral microbiota of male partners of women with BV was significantly more similar to the vaginal microbiota of their female partner compared to the vaginal microbiota of non-partner women with BV. This was not the case for male partners of women with normal vaginal microbiota. Specific BV-associated species were concordant in women with BV and their male partners. In monogamous heterosexual couples in which the woman has BV, the significantly higher similarity between the vaginal microbiota and the penile skin and urethral microbiota of the male partner, supports the hypothesis that sexual exchange of BV-associated bacterial taxa is common.This work was supported by National Institute of Health Grant R01 AI079071-01A1

Burden of SARS-CoV-2 infection in healthcare workers during second wave in England and impact of vaccines : prospective multicentre cohort study (SIREN) and mathematical model

Funding: The study is funded by the Department of Health and Social Care (DHSC) and UK Health Security Agency (UKHSA; formally Public Health England), with contributions from the governments of Northern Ireland, Scotland, and Wales. Funding was also provided by the National Institute for Health Research (NIHR) as an Urgent Public Health Priority Study and through the Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance (NIHR200915), a partnership between UKHSA and the University of Oxford.OBJECTIVE: To describe the incidence of, risk factors for, and impact of vaccines on primary SARS-CoV-2 infection during the second wave of the covid-19 pandemic in susceptible hospital healthcare workers in England. DESIGN: Multicentre prospective cohort study. SETTING: National Health Service secondary care health organisations (trusts) in England between 1 September 2020 and 30 April 2021. PARTICIPANTS: Clinical, support, and administrative staff enrolled in the SARS-CoV-2 Immunity and Reinfection Evaluation (SIREN) study with no evidence of previous infection. Vaccination status was obtained from national covid-19 vaccination registries and self-reported. MAIN OUTCOME MEASURE: SARS-CoV-2 infection confirmed by polymerase chain reaction. Mixed effects logistic regression was conducted to determine demographic and occupational risk factors for infection, and an individual based mathematical model was used to predict how large the burden could have been if vaccines had not been available from 8 December 2020 . RESULTS: During England's second wave, 12.9% (2353/18 284) of susceptible SIREN participants became infected with SARS-CoV-2. Infections peaked in late December 2020 and decreased from January 2021, concurrent with the cohort's rapid vaccination coverage and a national lockdown. In multivariable analysis, factors increasing the likelihood of infection in the second wave were being under 25 years old (20.3% (132/651); adjusted odds ratio 1.35, 95% confidence interval 1.07 to 1.69), living in a large household (15.8% (282/1781); 1.54, 1.23 to 1.94, for participants from households of five or more people), having frequent exposure to patients with covid-19 (19.2% (723/3762); 1.79, 1.56 to 2.06, for participants with exposure every shift), working in an emergency department or inpatient ward setting (20.8% (386/1855); 1.76, 1.45 to 2.14), and being a healthcare assistant (18.1% (267/1479); 1.43, 1.16 to 1.77). Time to first vaccination emerged as being strongly associated with infection (P<0.001), with each additional day multiplying a participant's adjusted odds ratio by 1.02. Mathematical model simulations indicated that an additional 9.9% of all patient facing hospital healthcare workers would have been infected were it not for the rapid vaccination coverage. CONCLUSIONS: The rapid covid-19 vaccine rollout from December 2020 averted infection in a large proportion of hospital healthcare workers in England: without vaccines, second wave infections could have been 69% higher. With booster vaccinations being needed for adequate protection from the omicron variant, and perhaps the need for further boosters for future variants, ensuring equitable delivery to healthcare workers is essential. The findings also highlight occupational risk factors that persisted in healthcare workers despite vaccine rollout; a greater understanding of the transmission dynamics responsible for these is needed to help to optimise the infection prevention and control policies that protect healthcare workers from infection and therefore to support staffing levels and maintain healthcare provision. TRIAL REGISTRATION: ISRCTN registry ISRCTN11041050.Publisher PDFPeer reviewe

Dynamic modelling of local fuel inventory and desorption in the whole tokamak vacuum vessel for auto-consistent plasma-wall interaction simulations

An extension of the SolEdge2D-EIRENE code package, named D-WEE, has been developed to add the dynamics of thermal desorption of hydrogen isotopes from the surface of plasma facing materials. To achieve this purpose, D-WEE models hydrogen isotopes implantation, transport and retention in those materials. Before launching autoconsistent simulation (with feedback of D-WEE on SolEdge2D-EIRENE), D-WEE has to be initialised to ensure a realistic wall behaviour in terms of dynamics (pumping or fuelling areas) and fuel content. A methodology based on modelling is introduced to perform such initialisation. A synthetic plasma pulse is built from consecutive SolEdge2D-EIRENE simulations. This synthetic pulse is used as a plasma background for the D-WEE module. A sequence of plasma pulses is simulated with D-WEE to model a tokamak operation. This simulation enables to extract at a desired time during a pulse the local fuel inventory and the local desorption flux density which could be used as initial condition for coupled plasma-wall simulations. To assess the relevance of the dynamic retention behaviour obtained in the simulation, a confrontation to post-pulse experimental pressure measurement is performed. Such confrontation reveals a qualitative agreement between the temporal pressure drop obtained in the simulation and the one observed experimentally. The simulated dynamic retention during the consecutive pulses is also studied.Peer reviewe

A machine learning approach based on generative topographic mapping for disruption prevention and avoidance at JET

The need for predictive capabilities greater than 95% with very limited false alarms are demanding requirements for reliable disruption prediction systems in tokamaks such as JET or, in the near future, ITER. The prediction of an upcoming disruption must be provided sufficiently in advance in order to apply effective disruption avoidance or mitigation actions to prevent the machine from being damaged. In this paper, following the typical machine learning workflow, a generative topographic mapping (GTM) of the operational space of JET has been built using a set of disrupted and regularly terminated discharges. In order to build the predictive model, a suitable set of dimensionless, machine-independent, physics-based features have been synthesized, which make use of 1D plasma profile information, rather than simple zero-D time series. The use of such predicting features, together with the power of the GTM in fitting the model to the data, obtains, in an unsupervised way, a 2D map of the multi-dimensional parameter space of JET, where it is possible to identify a boundary separating the region free from disruption from the disruption region. In addition to helping in operational boundaries studies, the GTM map can also be used for disruption prediction exploiting the potential of the developed GTM toolbox to monitor the discharge dynamics. Following the trajectory of a discharge on the map throughout the different regions, an alarm is triggered depending on the disruption risk of these regions. The proposed approach to predict disruptions has been evaluated on a training and an independent test set and achieves very good performance with only one tardive detection and a limited number of false detections. The warning times are suitable for avoidance purposes and, more important, the detections are consistent with physical causes and mechanisms that destabilize the plasma leading to disruptions.Peer reviewe

Beryllium global erosion and deposition at JET-ILW simulated with ERO2.0

The recently developed Monte-Carlo code ERO2.0 is applied to the modelling of limited and diverted discharges at JET with the ITER-like wall (ILW). The global beryllium (Be) erosion and deposition is simulated and compared to experimental results from passive spectroscopy. For the limiter configuration, it is demonstrated that Be self-sputtering is an important contributor (at least 35%) to the Be erosion. Taking this contribution into account, the ERO2.0 modelling confirms previous evidence that high deuterium (D) surface concentrations of up to similar to 50% atomic fraction provide a reasonable estimate of Be erosion in plasma-wetted areas. For the divertor configuration, it is shown that drifts can have a high impact on the scrape-off layer plasma flows, which in turn affect global Be transport by entrainment and lead to increased migration into the inner divertor. The modelling of the effective erosion yield for different operational phases (ohmic, L- and H-mode) agrees with experimental values within a factor of two, and confirms that the effective erosion yield decreases with increasing heating power and confinement.Peer reviewe