Metabolic dysfunction Associated Steatotic Liver Disease (MASLD) outcomes such as MASH (metabolic dysfunction associated steatohepatitis), fibrosis and cirrhosis are ordinarily determined by ...resource-intensive and invasive biopsies. We aim to show that routine clinical tests offer sufficient information to predict these endpoints.
Using the LITMUS Metacohort derived from the European NAFLD Registry, the largest MASLD dataset in Europe, we create three combinations of features which vary in degree of procurement including a 19-variable feature set that are attained through a routine clinical appointment or blood test. This data was used to train predictive models using supervised machine learning (ML) algorithm XGBoost, alongside missing imputation technique MICE and class balancing algorithm SMOTE. Shapley Additive exPlanations (SHAP) were added to determine relative importance for each clinical variable.
Analysing nine biopsy-derived MASLD outcomes of cohort size ranging between 5385 and 6673 subjects, we were able to predict individuals at training set AUCs ranging from 0.719-0.994, including classifying individuals who are At-Risk MASH at an AUC = 0.899. Using two further feature combinations of 26-variables and 35-variables, which included composite scores known to be good indicators for MASLD endpoints and advanced specialist tests, we found predictive performance did not sufficiently improve. We are also able to present local and global explanations for each ML model, offering clinicians interpretability without the expense of worsening predictive performance.
This study developed a series of ML models of accuracy ranging from 71.9-99.4% using only easily extractable and readily available information in predicting MASLD outcomes which are usually determined through highly invasive means.
Environmental DNA (eDNA) has been increasingly utilized by academic, industry, and government groups for environmental monitoring due to its efficiency in regards to both time and cost, as well as ...non‐invasiveness to target organisms, and reduced dependency on trained biologists for sample collection. The methods typically employ quantitative real‐time polymerase chain reaction (qPCR) to detect the presence of a given organism's DNA in a sample. Currently, there is a drive to use qPCR data to infer biomass or abundance by quantitating the copy number or concentration of a given target gene fragment in a sample, which is often very dilute. Before eDNA can be fully accepted as an environmental decision‐making tool, however, certain aspects of the methods require standardization, including the quantification of target DNA in low copy number samples. Models that are not able to properly make use of data from highly dilute samples are severely hampered in their definitions of the limits of detection and quantification at the lower end of the detection curve. We propose a statistical model for a standard curve that relates the number of qPCR‐detected technical replicates to the copy number in the case of low copy number samples. Likelihood methods are used to estimate the parameters of the model and we derive inverse regression estimates together with their standard errors. Limits of copy number detection and quantification, and their confidence intervals are derived using a well‐accepted statistical approach thus providing a more broadly applicable and robust method for reporting eDNA abundance into the low copy number range. The method is illustrated using experimental results from multiple laboratories.
We propose a statistical model for a standard curve that relates the number of qPCR detected technical replicates to the copy number in the case of low copy number eDNA samples. Limits of copy number detection and quantification and their confidence intervals are derived using a well accepted statistical hypothesis testing approach thus providing a broadly applicable and robust method for reporting eDNA abundance into the low copy number range.
Alcohol-related liver disease (ALD) remains a leading cause of liver-related morbidity and mortality. Age, fibrosis stage, MELD score and continued alcohol consumption predict outcome in everyday ...clinical practice. In previous studies increased hepatocyte nuclear area and hepatocyte expression of p21, both markers of senescence, were associated with increased fibrosis stage and a poor outcome in non-alcohol-related fatty liver disease, while increased hepatocyte nuclear area was related to liver dysfunction in ALD cirrhosis. This study, therefore, investigated the pattern of hepatocyte cell cycle phase distribution and hepatocyte p21 expression in relation to outcome in ALD.
Liver sections from two cohorts were studied. The first comprised 42 patients across the full spectrum of ALD. The second cohort comprised 77 patients with ALD cirrhosis. Immunohistochemistry assessed hepatocyte expression of cell cycle phase markers and p21. Regenerating liver (n=12) and "normal" liver sections (n=5) served as positive and negative controls, respectively.
In the first cohort there was little cell cycle progression beyond G1/S phase and increased hepatocyte p21 expression (p<0.0001), which correlated independently with fibrosis stage (p=0.005) and an adverse liver-related outcome (p=0.03). In the second cohort, both hepatocyte p21 expression (p<0.001) and MELD score (p=0.006) were associated independently with an adverse liver-related outcome; this association was stronger with hepatocyte p21 expression (AUROC 0.74; p=0.0002) than with MELD score (AUROC 0.59; p=0.13). Further, hepatocyte p21 expression co-localised with increased hepatic stellate cell activation.
The findings are consistent with impaired cell cycle progression beyond the G1/S phase in ALD. The striking independent associations between increased hepatocyte p21 expression and both fibrosis stage and an adverse liver-related outcome in both cohorts suggests hepatocyte senescence plays an important role in ALD. Measuring hepatocyte p21 expression is simple and cheap and in this series was a useful measure of long-term prognosis in ALD.
Over the last several decades, numerous civil wars have ended as a consequence of negotiated settlements. Following many of these settlements, rebel groups have made the transition to political party ...and competed in democratic elections. In this paper, I assess the legacy of civil war on the performance of rebel groups as political parties. I argue that the ability of rebels to capture and control territory and their use of violence against the civilian population are two key factors explaining the performance of rebels as political parties. I test these hypotheses against the case of the Farabundo Martí National Liberation Front (FMLN) in El Salvador using one-way ANOVA and multivariate regression analyses. In analyzing the FMLN’s performance in the 1994 “elections of the century,” I find that, as a political party, the FMLN benefited both from the state’s violently disproportionate response and its ability to hold territory during the war.
Non-alcoholic steatohepatitis (NASH) is characterized by lipotoxicity, inflammation and fibrosis, ultimately leading to end-stage liver disease. The molecular mechanisms promoting NASH are poorly ...understood, and treatment options are limited. Here, we demonstrate that hepatic expression of bone morphogenetic protein 8B (BMP8B), a member of the transforming growth factor beta (TGFβ)-BMP superfamily, increases proportionally to disease stage in people and animal models with NASH. BMP8B signals via both SMAD2/3 and SMAD1/5/9 branches of the TGFβ-BMP pathway in hepatic stellate cells (HSCs), promoting their proinflammatory phenotype. In vivo, the absence of BMP8B prevents HSC activation, reduces inflammation and affects the wound-healing responses, thereby limiting NASH progression. Evidence is featured in primary human 3D microtissues modelling NASH, when challenged with recombinant BMP8. Our data show that BMP8B is a major contributor to NASH progression. Owing to the near absence of BMP8B in healthy livers, inhibition of BMP8B may represent a promising new therapeutic avenue for NASH treatment.
Donation after circulatory death (DCD) liver transplantation is associated with higher rates of graft loss. In this paper, we explored whether the Model for Early Allograft Function (MEAF) predicted ...outcome in DCD liver transplantation. We performed a retrospective analysis of prospectively collected data from all adult DCD (Maastricht 3) livers transplanted in Cambridge and Edinburgh between 1 January 2011 and 30 June 2017, excluding those undergoing any form of machine perfusion. 187 DCD liver transplants were performed during the study period. DCD liver transplants with a lower MEAF score had a significantly better survival compared to those with a high MEAF score (Mantel‐Cox P < .0001); this was largely due to early graft loss. Beyond 28 days post‐transplant, there were no significant long‐term graft or patient survival differences irrespective of the grade of MEAF (Mantel‐Cox P = .64 and P = .43, respectively). The MEAF score correlated with the length of ICU (P = .0011) and hospital stay (P = .0007), but did not predict the requirement for retransplantation for ischemic cholangiopathy (P = .37) or readmission (P = .74). In this study, a high MEAF score predicted early graft loss, but not the subsequent need for re‐transplantation or late graft failure as a result of intrahepatic ischemic bile duct pathology.
The term 'zero tolerance' has recently been applied to healthcare-associated infections, implying that such events are always preventable. This may not be the case for healthcare-associated ...infections such as methicillin-resistant Staphylococcus aureus (MRSA) bacteraemia.
We combined information from an epidemiological investigation and bacterial whole-genome sequencing to evaluate a cluster of five MRSA bacteraemia episodes in four patients in a specialist hepatology unit.
The five MRSA bacteraemia isolates were highly related by multilocus sequence type (ST) (four isolates were ST22 and one isolate was a single-locus variant, ST2046). Whole-genome sequencing demonstrated unequivocally that the bacteraemia cases were unrelated. Placing the MRSA bacteraemia isolates within a local and global phylogenetic tree of MRSA ST22 genomes demonstrated that the five bacteraemia isolates were highly diverse. This was consistent with the acquisition and importation of MRSA from the wider referral network. Analysis of MRSA carriage and disease in patients within the hepatology service demonstrated a higher risk of both initial MRSA acquisition compared with the nephrology service and a higher risk of progression from MRSA carriage to bacteraemia, compared with patients in nephrology or geriatric services. A root cause analysis failed to reveal any mechanism by which three of five MRSA bacteraemia episodes could have been prevented.
This study illustrates the complex nature of MRSA carriage and bacteraemia in patients in a specialized hepatology unit. Despite numerous ongoing interventions to prevent MRSA bacteraemia in healthcare settings, these are unlikely to result in a zero incidence in referral centres that treat highly complex patients.
Due to a symbiotic relationship, economic growth leads to greater energy consumption in transportation, manufacturing, and domestic sectors. Electricity consumption in the global south is rising as ...nations in the region strive for economic development. Due to the high costs of fossil fuels and environmental issues, these countries are planning exploitation of their renewable energy potential for meeting their energy needs. In this paper, we take Myanmar as a case study for which photovoltaic (PV) is seen as the preferred technology owing to its modular nature and Myanmar’s tremendous PV potential. To create sustainable systems, the impact of diurnal PV profiles on electricity demand profiles needs investigating. Accurate load forecasts lead to significant savings in operation and planning and maintenance. Artificial neural networks (ANNs) can easily be used for load profile forecasting. This work proposes a three-stage systematic approach which could be employed by global south countries for designing ANN load forecasting models with the aim of simplifying the design process. While the results of this work demonstrate that PV is a suitable energy source for countries like Myanmar, they also point to the importance of including annual load increase rate and PV output degradation rate in system planning.
Several magnetic resonance parallel imaging techniques require explicit estimates of the receive coil sensitivity profiles. These estimates must be accurate over both the object and its surrounding ...regions to avoid generating artifacts in the reconstructed images. Regularized estimation methods that involve minimizing a cost function containing both a data-fit term and a regularization term provide robust sensitivity estimates. However, these methods can be computationally expensive when dealing with large problems. In this paper, we propose an iterative algorithm based on variable splitting and the augmented Lagrangian method that estimates the coil sensitivity profile by minimizing a quadratic cost function. Our method, ADMM-Circ, reformulates the finite differencing matrix in the regularization term to enable exact alternating minimization steps. We also present a faster variant of this algorithm using intermediate updating of the associated Lagrange multipliers. Numerical experiments with simulated and real data sets indicate that our proposed method converges approximately twice as fast as the preconditioned conjugate gradient method over the entire field-of-view. These concepts may accelerate other quadratic optimization problems.
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