Limitations of the MELD score in predicting mortality or need for removal from waiting list in patients awaiting liver transplantation

<p>Abstract</p> <p>Background</p> <p>Decompensated cirrhosis is associated with a poor prognosis and liver transplantation provides the only curative treatment option with excellent long-term results. The relative shortage of organ donors renders the allocation algorithms of organs essential. The optimal strategy based on scoring systems and/or waiting time is still under debate.</p> <p>Methods</p> <p>Data sets of 268 consecutive patients listed for single-organ liver transplantation for nonfulminant liver disease between 2003 and 2005 were included into the study. The Model for End-Stage Liver Disease (MELD) and Child-Turcotte-Pugh (CTP) scores of all patients at the time of listing were used for calculation. The predictive ability not only for mortality on the waiting list but also for the need for withdrawal from the waiting list was calculated for both scores. The Mann-Whitney-U Test was used for the univariate analysis and the AUC-Model for discrimination of the scores.</p> <p>Results</p> <p>In the univariate analysis comparing patients who are still on the waiting list and patients who died or were removed from the waiting list due to poor conditions, the serum albumin, bilirubin INR, and CTP and MELD scores as well as the presence of ascites and encephalopathy were significantly different between the groups (p < 0.05), whereas serum creatinine and urea showed no difference.</p> <p>Comparing the predictive abilities of CTP and MELD scores, the best discrimination between patients still alive on the waiting list and patients who died on or were removed from the waiting list was achieved at a CTP score of ≥9 and a MELD score of ≥14.4. The sensitivity and specificity to identify mortality or severe deterioration for CTP was 69.0% and 70.5%, respectively; for MELD, it was 62.1% and 72.7%, respectively. This result was supported by the AUC analysis showing a strong trend for superiority of CTP over MELD scores (AUROC 0.73 and 0.68, resp.; p = 0.091).</p> <p>Conclusion</p> <p>The long term prediction of mortality or removal from waiting list in patients awaiting liver transplantation might be better assessed by the CTP score than the MELD score. This might have implications for the development of new improved scoring systems.</p

Global shortage of technical agars: back to basics (resource management)

Bacteriological and technical agars are in short supply with potential consequences for research, public health, and clinical labs around the world. To diagnose bottlenecks and sustainability problems that may be putting the industry at risk, we analyzed the available time series for the global landings of Gelidium, the most important raw materials for the industry. Data on the harvest of Gelidium spp. have been reported since1912, when Japan was the only producer. After World War II the diversification of harvested species and producing countries resulted in a strong increase in global landings. Maximum harvest yields of almost 60,000 t year(-1) in the 1960s were sustained until the 1980s, after which landings decreased continuously to the present. In the 2010s, a reduction in the global production to about 25,000 t year(-1) was observed, which was lower than the yields of the 1950s. Landings by important producers such as Japan, Korea, Spain, and Portugal have collapsed. This is the ultimate cause of the present shortage of bacteriological and technical agars. However, an important factor at play is the concentration of the global landings of Gelidium in Morocco, as its relative contribution increased from 23% in the 1960s to the present 82%. Two specific bottlenecks were identified: restrictive export quotas of unprocessed Gelidium in favor of the national agar industry and resource management regulations that were apparently not enforced resulting in over-harvesting and resource decline. The global industry may well be dependent on resource management basics. Simple harvest statistics must be gathered such as the harvest effort and the variation of harvest yields along the harvest season. We discuss how this information is fundamental to manage the resource. The available harvest statistics are generally poor and limited and vary significantly among different sources of data. Probable confusions between dry and wet weight reporting and poor discrimination of the species harvested need to be resolved

Genome wide analysis of gene expression changes in skin from patients with type 2 diabetes

Non-healing chronic ulcers are a serious complication of diabetes and are a major healthcare problem. While a host of treatments have been explored to heal or prevent these ulcers from forming, these treatments have not been found to be consistently effective in clinical trials. An understanding of the changes in gene expression in the skin of diabetic patients may provide insight into the processes and mechanisms that precede the formation of non-healing ulcers. In this study, we investigated genome wide changes in gene expression in skin between patients with type 2 diabetes and non-diabetic patients using next generation sequencing. We compared the gene expression in skin samples taken from 27 patients (13 with type 2 diabetes and 14 non-diabetic). This information may be useful in identifying the causal factors and potential therapeutic targets for the prevention and treatment of diabetic related diseases

Leaching as a pretreatment process to complement torrefaction in improving co-firing characteristics of Jatropha curcas seed cake

The presence of certain inorganic elements in biomass causes issues such as slagging, fouling and corrosion when co-firing with coal for power generation. In this work, the efficacy of leaching to remove these elements from Jatropha curcas seed cake was investigated. Leaching of both untorrefied and torrefied seed cakes was carried out in Milli-Q water at temperatures of 20, 35 and 50 °C. At 20 °C, the two critical elements, potassium and chlorine, decreased by as much as 85 and 97 %, respectively. Leaching at higher temperatures was only beneficial for the more intensely torrefied biomass, since they were more resistant to leaching. The electrical conductivity and ion content of the leachates were measured, as were the inorganic elemental content, dry ash content, volatile matter content and higher heating value (HHV) of the solid seed cake. A secondary benefit of the leaching was an increase in the HHV by up to 10 %

Decoding Unattended Fearful Faces with Whole-Brain Correlations: An Approach to Identify Condition-Dependent Large-Scale Functional Connectivity

Processing of unattended threat-related stimuli, such as fearful faces, has been previously examined using group functional magnetic resonance (fMRI) approaches. However, the identification of features of brain activity containing sufficient information to decode, or “brain-read”, unattended (implicit) fear perception remains an active research goal. Here we test the hypothesis that patterns of large-scale functional connectivity (FC) decode the emotional expression of implicitly perceived faces within single individuals using training data from separate subjects. fMRI and a blocked design were used to acquire BOLD signals during implicit (task-unrelated) presentation of fearful and neutral faces. A pattern classifier (linear kernel Support Vector Machine, or SVM) with linear filter feature selection used pair-wise FC as features to predict the emotional expression of implicitly presented faces. We plotted classification accuracy vs. number of top N selected features and observed that significantly higher than chance accuracies (between 90–100%) were achieved with 15–40 features. During fearful face presentation, the most informative and positively modulated FC was between angular gyrus and hippocampus, while the greatest overall contributing region was the thalamus, with positively modulated connections to bilateral middle temporal gyrus and insula. Other FCs that predicted fear included superior-occipital and parietal regions, cerebellum and prefrontal cortex. By comparison, patterns of spatial activity (as opposed to interactivity) were relatively uninformative in decoding implicit fear. These findings indicate that whole-brain patterns of interactivity are a sensitive and informative signature of unattended fearful emotion processing. At the same time, we demonstrate and propose a sensitive and exploratory approach for the identification of large-scale, condition-dependent FC. In contrast to model-based, group approaches, the current approach does not discount the multivariate, joint responses of multiple functional connections and is not hampered by signal loss and the need for multiple comparisons correction

The role of the amygdala in face perception and evaluation

Faces are one of the most significant social stimuli and the processes underlying face perception are at the intersection of cognition, affect, and motivation. Vision scientists have had a tremendous success of mapping the regions for perceptual analysis of faces in posterior cortex. Based on evidence from (a) single unit recording studies in monkeys and humans; (b) human functional localizer studies; and (c) meta-analyses of neuroimaging studies, I argue that faces automatically evoke responses not only in these regions but also in the amygdala. I also argue that (a) a key property of faces represented in the amygdala is their typicality; and (b) one of the functions of the amygdala is to bias attention to atypical faces, which are associated with higher uncertainty. This framework is consistent with a number of other amygdala findings not involving faces, suggesting a general account for the role of the amygdala in perception

On the relevance of preprocessing in predictive maintenance for dynamic systems

The complexity involved in the process of real-time data-driven monitoring dynamic systems for predicted maintenance is usually huge. With more or less in-depth any data-driven approach is sensitive to data preprocessing, understood as any data treatment prior to the application of the monitoring model, being sometimes crucial for the final development of the employed monitoring technique. The aim of this work is to quantify the sensitiveness of data-driven predictive maintenance models in dynamic systems in an exhaustive way. We consider a couple of predictive maintenance scenarios, each of them defined by some public available data. For each scenario, we consider its properties and apply several techniques for each of the successive preprocessing steps, e.g. data cleaning, missing values treatment, outlier detection, feature selection, or imbalance compensation. The pretreatment configurations, i.e. sequential combinations of techniques from different preprocessing steps, are considered together with different monitoring approaches, in order to determine the relevance of data preprocessing for predictive maintenance in dynamical systems

Regional research priorities in brain and nervous system disorders

The characteristics of neurological, psychiatric, developmental and substance-use disorders in low-and middle-income countries are unique and the burden that they have will be different from country to country. Many of the differences are explained by the wide variation in population demographics and size, poverty, conflict, culture, land area and quality, and genetics. Neurological, psychiatric, developmental and substance-use disorders that result from, or are worsened by, a lack of adequate nutrition and infectious disease still afflict much of sub-Saharan Africa, although disorders related to increasing longevity, such as stroke, are on the rise. In the Middle East and North Africa, major depressive disorders and post-traumatic stress disorder are a primary concern because of the conflict-ridden environment. Consanguinity is a serious concern that leads to the high prevalence of recessive disorders in the Middle East and North Africa and possibly other regions. The burden of these disorders in Latin American and Asian countries largely surrounds stroke and vascular disease, dementia and lifestyle factors that are influenced by genetics. Although much knowledge has been gained over the past 10 years, the epidemiology of the conditions in low-and middle-income countries still needs more research. Prevention and treatments could be better informed with more longitudinal studies of risk factors. Challenges and opportunities for ameliorating nervous-system disorders can benefit from both local and regional research collaborations. The lack of resources and infrastructure for health-care and related research, both in terms of personnel and equipment, along with the stigma associated with the physical or behavioural manifestations of some disorders have hampered progress in understanding the disease burden and improving brain health. Individual countries, and regions within countries, have specific needs in terms of research priorities.Fil: Ravindranath, Vijayalakshmi. Indian Institute of Science; IndiaFil: Dang, Hoang Minh. Vietnam National University; VietnamFil: Goya, Rodolfo Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Bioquímicas de La Plata ; ArgentinaFil: Mansour, Hader. University of Pittsburgh; Estados Unidos. Mansoura University; EgiptoFil: Nimgaonkar, Vishwajit L.. University of Pittsburgh; Estados UnidosFil: Russell, Vivienne Ann. University of Cape Town; SudáfricaFil: Xin, Yu. Peking University; Chin

PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study

BACKGROUND: Statin treatment and variants in the gene encoding HMG-CoA reductase are associated with reductions in both the concentration of LDL cholesterol and the risk of coronary heart disease, but also with modest hyperglycaemia, increased bodyweight, and modestly increased risk of type 2 diabetes, which in no way offsets their substantial benefits. We sought to investigate the associations of LDL cholesterol-lowering PCSK9 variants with type 2 diabetes and related biomarkers to gauge the likely effects of PCSK9 inhibitors on diabetes risk. METHODS: In this mendelian randomisation study, we used data from cohort studies, randomised controlled trials, case control studies, and genetic consortia to estimate associations of PCSK9 genetic variants with LDL cholesterol, fasting blood glucose, HbA1c, fasting insulin, bodyweight, waist-to-hip ratio, BMI, and risk of type 2 diabetes, using a standardised analysis plan, meta-analyses, and weighted gene-centric scores. FINDINGS: Data were available for more than 550 000 individuals and 51 623 cases of type 2 diabetes. Combined analyses of four independent PCSK9 variants (rs11583680, rs11591147, rs2479409, and rs11206510) scaled to 1 mmol/L lower LDL cholesterol showed associations with increased fasting glucose (0·09 mmol/L, 95% CI 0·02 to 0·15), bodyweight (1·03 kg, 0·24 to 1·82), waist-to-hip ratio (0·006, 0·003 to 0·010), and an odds ratio for type diabetes of 1·29 (1·11 to 1·50). Based on the collected data, we did not identify associations with HbA1c (0·03%, -0·01 to 0·08), fasting insulin (0·00%, -0·06 to 0·07), and BMI (0·11 kg/m(2), -0·09 to 0·30). INTERPRETATION: PCSK9 variants associated with lower LDL cholesterol were also associated with circulating higher fasting glucose concentration, bodyweight, and waist-to-hip ratio, and an increased risk of type 2 diabetes. In trials of PCSK9 inhibitor drugs, investigators should carefully assess these safety outcomes and quantify the risks and benefits of PCSK9 inhibitor treatment, as was previously done for statins. FUNDING: British Heart Foundation, and University College London Hospitals NHS Foundation Trust (UCLH) National Institute for Health Research (NIHR) Biomedical Research Centre.This work was supported by a British Heart Foundation Programme Grant (RG/10/12/28456). AFS is funded by University College London Hospitals NHS Foundation Trust (UCLH) National Institute for Health Research (NIHR) Biomedical Research Centre (BRC10200) and by a UCL springboard population science fellowship. FWA is supported by a Dekker scholarship-Junior Staff Member 2014T001–Netherlands Heart Foundation and UCL Hospitals NIHR Biomedical Research Centre. ADH is an NIHR Senior Investigator. Funding information and acknowledgments for studies contributing data are reported in the appendix