Palliative Care for Patients with End-Stage Liver Disease on the Liver Transplant Waiting List: An International Systematic Review

People with end-stage liver disease on the liver transplant waiting list have high symptom burden, which can successfully be addressed by specialist palliative care. Potential tensions with the perceived curative nature of liver transplant make delivering specialist palliative care challenging. This systematic review seeks to establish what is known on the impact of specialist palliative care for patients on liver transplant waiting lists, healthcare professionals' perspectives of providing specialist palliative care for this population, and uptake of advance care planning (ACP). Medline, Embase, and CINAHL were searched to May 5, 2020. Qualitative and quantitative findings were grouped together according to main relevant themes. Eight studies of mixed quality and mainly quantitative, were identified. Findings suggest early palliative care intervention improve patients' symptoms and prompt ACP conversations, but patients on the waiting list receive limited palliative care input. Liver physicians' lack of clarity on referral criteria and liver transplant patients' concerns of being abandoned, were reasons for reluctance to refer to specialist palliative care. They felt referral to specialist palliative care is appropriate only for patients receiving hospice or end of life care. Uptake and understanding of ACP and goals of care designation by patients is poor. This review found evidence of benefit of specialist palliative care for patients on liver transplant waiting lists, but found in a limited understanding of their role. Evidence is limited to studies from North America. Future research is needed to understand better how palliative care could be provided into this clinical environment

Background risk of breast cancer and the association between physical activity and mammographic density

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Performance Analysis of Effective Methods for Solving Band Matrix SLAEs after Parabolic Nonlinear PDEs

This paper presents an experimental performance study of implementations of three different types of algorithms for solving band matrix systems of linear algebraic equations (SLAEs) after parabolic nonlinear partial differential equations -- direct, symbolic, and iterative, the former two of which were introduced in Veneva and Ayriyan (arXiv:1710.00428v2). An iterative algorithm is presented -- the strongly implicit procedure (SIP), also known as the Stone method. This method uses the incomplete LU (ILU(0)) decomposition. An application of the Hotelling-Bodewig iterative algorithm is suggested as a replacement of the standard forward-backward substitutions. The upsides and the downsides of the SIP method are discussed. The complexity of all the investigated methods is presented. Performance analysis of the implementations is done using the high-performance computing (HPC) clusters "HybriLIT" and "Avitohol". To that purpose, the experimental setup and the results from the conducted computations on the individual computer systems are presented and discussed.Comment: 10 pages, 2 figure

Sebomic identification of sex- and ethnicity-specific variations in residual skin surface components (RSSC) for bio-monitoring or forensic applications

Background: “Residual skin surface components” (RSSC) is the collective term used for the superficial layer of sebum, residue of sweat, small quantities of intercellular lipids and components of natural moisturising factor present on the skin surface. Potential applications of RSSC include use as a sampling matrix for identifying biomarkers of disease, environmental exposure monitoring, and forensics (retrospective identification of exposure to toxic chemicals). However, it is essential to first define the composition of “normal” RSSC. Therefore, the aim of the current study was to characterise RSSC to determine commonalities and differences in RSSC composition in relation to sex and ethnicity. Methods: Samples of RSSC were acquired from volunteers using a previously validated method and analysed by high-pressure liquid chromatography–atmospheric pressure chemical ionisation–mass spectrometry (HPLC-APCI-MS). The resulting data underwent sebomic analysis. Results: The composition and abundance of RSSC components varied according to sex and ethnicity. The normalised abundance of free fatty acids, wax esters, diglycerides and triglycerides was significantly higher in males than females. Ethnicity-specific differences were observed in free fatty acids and a diglyceride. Conclusions: The HPLC-APCI-MS method developed in this study was successfully used to analyse the normal composition of RSSC. Compositional differences in the RSSC can be attributed to sex and ethnicity and may reflect underlying factors such as diet, hormonal levels and enzyme expression.Peer reviewedFinal Published versio

Sensory Attenuation Assessed by Sensory Evoked Potentials in Functional Movement Disorders.

BACKGROUND: Functional (psychogenic) movement disorders (FMD) have features associated with voluntary movement (e.g. distractibility) but patients report movements to be out of their control. One explanation for this phenomenon is that sense of agency for movement is impaired. The phenomenon of reduction in the intensity of sensory experience when movement is self-generated and a reduction in sensory evoked potentials (SEPs) amplitude at the onset of self-paced movement (sensory attenuation) have been linked to sense of agency for movement. METHODS: We compared amplitude of SEPs from median nerve stimulation at rest and at the onset of a self-paced movement of the thumb in 17 patients with FMD and 17 healthy controls. RESULTS: Patients showed lack of attenuation of SEPs at the onset of movement compared to reduction in amplitude of SEPs in controls. FMD patients had significantly different ratios of movement onset to rest SEPs than did healthy controls at each electrode: 0.79 in healthy controls and 1.35 in patients at F3 (t = -4.22, p<0.001), 0.78 in healthy controls and 1.12 at patients C3 (t = -3.15, p = 0.004) and 0.77 in healthy controls and 1.05 at patients P3 (t = -2.88, p = 0.007). CONCLUSIONS: Patients with FMD have reduced sensory attenuation as measured by SEPs at onset of self-paced movement. This finding can be plausibly linked to impairment of sense of agency for movement in these patients

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Criminal and Noncriminal Psychopathy: The Devil is in the Detail

Brooks, NS ORCiD: 0000-0003-1784-099XPsychopathy is prevalent and problematic in criminal populations, but is also found to be present in noncriminal populations. In 1992, Robert Hare declared that psychopaths may also “be found in the boardroom”, which has since been followed by an interest in the issue of noncriminal, or even successful, psychopathy. In this chapter, the paradox of criminal and noncriminal psychopathy is discussed with specific attention given to the similarities and differences that account for psychopathic personality across contexts. That psychopathy is a condition typified by a constellation of traits and behaviours requires wider research across diverse populations, and thus the streams of research related to criminal and noncriminal psychopathy are presented and the implications of these contrasting streams are explored

Hedgehog pathway mutations drive oncogenic transformation in high-risk T-cell acute lymphoblastic leukemia.

The role of Hedgehog signaling in normal and malignant T-cell development is controversial. Recently, Hedgehog pathway mutations have been described in T-ALL, but whether mutational activation of Hedgehog signaling drives T-cell transformation is unknown, hindering the rationale for therapeutic intervention. Here, we show that Hedgehog pathway mutations predict chemotherapy resistance in human T-ALL, and drive oncogenic transformation in a zebrafish model of the disease. We found Hedgehog pathway mutations in 16% of 109 childhood T-ALL cases, most commonly affecting its negative regulator PTCH1. Hedgehog mutations were associated with resistance to induction chemotherapy (P = 0.009). Transduction of wild-type PTCH1 into PTCH1-mutant T-ALL cells induced apoptosis (P = 0.005), a phenotype that was reversed by downstream Hedgehog pathway activation (P = 0.007). Transduction of most mutant PTCH1, SUFU, and GLI alleles into mammalian cells induced aberrant regulation of Hedgehog signaling, indicating that these mutations are pathogenic. Using a CRISPR/Cas9 system for lineage-restricted gene disruption in transgenic zebrafish, we found that ptch1 mutations accelerated the onset of notch1-induced T-ALL (P = 0.0001), and pharmacologic Hedgehog pathway inhibition had therapeutic activity. Thus, Hedgehog-activating mutations are driver oncogenic alterations in high-risk T-ALL, providing a molecular rationale for targeted therapy in this disease