Stratified medicine: an exploration of the utility of non-invasive serum markers for the management of chronic liver diseases

Chronic liver disease (CLD), the 3rd commonest cause of premature death in the UK, is detected late when interventions are often ineffective. Non-alcoholic fatty liver disease (NAFLD) and chronic hepatitis C (CHC) account for a significant proportion of CLD in the UK. Numerous direct (molecules involved in matrix biology) and indirect biomarkers (standard laboratory tests) have been successfully developed to detect advanced liver fibrosis. Less success, however, has been achieved in the detection of alternative diagnostic targets such as early stage fibrosis, non-alcoholic steatohepatitis (NASH) and fibrosis evolution. In a study of 17 candidate biomarkers amongst patients with NAFLD, terminal peptide of procollagen 3 was identified as the only biomarker demonstrating good performance for the detection of NASH in both a derivation and validation cohort. Thereafter, these results were further validated in another NAFLD cohort. In a study of 9 biomarkers (indirect and direct) in the detection of fibrosis in NAFLD, direct biomarkers demonstrated better diagnostic performance overall and for early stage fibrosis although some indirect biomarkers identified advanced fibrosis and cirrhosis with good effect. Thereafter, parallel and serial combinations of 3 biomarkers of advanced fibrosis were proposed and successfully employed in a cohort of patients with NAFLD to improve diagnostic performance. In a study of 10 biomarkers in CHC, fibrosis detection was enhanced using complex biomarker panels that incorporated direct tests. Of note, the use an alternative assay for a constituent component significantly affected biomarker panel performance both overall and at diagnostic thresholds. The ability of the biomarkers to monitor fibrosis evolution arising due to putative antifibrotic was then studied in CHC. In the first study, changes in direct biomarker, ELF, could predict fibrosis evolution. In the second study, an improvement of indirect biomarker scores in patients with CHC cirrhosis during treatment was found to denote an improved prognosis

What to do if standard therapy for hepatitis C fails

The standard of care for treatment of individuals chronically infected with hepatitis C virus is pegylated interferon in combination with ribavirin. Efficacy is closely related to viral genotype. This review outlines potential therapeutic strategies for treatment failures and discusses some of the newer agents currently in development

A Framework for Computerized Adaptive Assessment based on Trajectory Driven Pedagogy Implemented in an Engineering Course

Engineering education needs to be flexible with the changing technology, and it must blend traditional and new teaching pedagogy for the overall knowledge creation in the students. A survey of prevalent experiential learning methods has shown tremendous potential to improve engineering students' learning. However, existing experiential learning methods are hard to integrate with current teaching-learning process at Amity University, Uttar Pradesh, Lucknow Campus, India. A pilot study conducted during Power plant Instrumentation taught in the seventh semester of the Electrical and Electronics undergraduate program balances the current teaching method with the proposed Trajectory -driven pedagogy as an alternative teaching pedagogy. A trajectory driven computerized adaptive assessment procedure for teaching has been proposed in this paper. The system follows a trajectory of courses to generate the subsequent questions from the vast database of questions. A sequence of questions is guided by Concept Map which represents the questions from three courses in a hierarchical manner. Analysis of students' assessments shows that the proposed methodology could is accurate for quantitative measurement of the course learning outcomes in a summative assessment. &nbsp

Harmonic mitigation and power quality improvement in utility grid with solar energy penetration using distribution static compensator

Abstract Distribution static compensator is based on power electronic devices technology which is utilized to supply rapid changes in active power as well as reactive power of utility grids. This is useful to achieve corrections in power factor, balancing of load, compensation of current and filtering of harmonics. Therefore, proposed work investigates the improvement of the power quality by utilizing the distribution static compensator, which is equipped by battery energy storage system and interfaced to distribution network with solar photo voltaic (PV) energy integration. In the present study, distribution static compensator is controlled using a control strategy based on the synchronous reference frame theory. Customised IEEE‐13 nodes test system incorporating solar PV generation and distribution static compensator, is utilized to perform the harmonic mitigation and power quality analysis. Disturbances of power quality and harmonics have been investigated due to abrupt changes in the insolation of solar radiation, outage of PV plant from grid and synchronization of PV plant to grid. MATLAB/Simulink environment is utilized to perform the study. Effectiveness of a developed approach is validated by comparing results of simulation with results extracted in real time using real time digital simulator. Results indicate that the developed method is more effective for harmonic mitigation and improving power quality of electrical power in distribution network integrated with solar PV generation. Performance of the approach is compared with the performance of methods reported in the literature to establish the suitability of the method for harmonics mitigation and power quality improvement in grid with solar energy

The fate of indeterminate liver lesions: What proportion are precursors of hepatocellular carcinoma?

BACKGROUND: The natural history and incidence of hepatocellular carcinoma (HCC) arising from indeterminate liver lesions are not well described. We aimed to define the incidence of HCC in a cohort of patients undergoing surveillance by magnetic resonance imaging (MRI) and estimate any associations with incident HCC. METHODS: We performed a retrospective follow-up study, identifying MRI scans in which indeterminate lesions had been reported between January 2006 and January 2017. Subsequent MRI scan reports were reviewed for incident HCC arising from indeterminate lesions, data were extracted from electronic patient records and survival analysis performed to estimate associations with baseline factors. RESULTS: One hundred and nine patients with indeterminate lesions on MRI were identified. HCC developed in 19 (17%) patients over mean follow up of 4.6 years. Univariate Cox proportional hazards analysis found incident HCC to be significantly associated with baseline low platelet count (hazard ratio (HR) = 7.3 (95% confidence intervals (CI) 2.1-24.9), high serum alpha-fetoprotein level (HR = 2.7 (95% CI 1.0-7.1)) and alcohol consumption above fourteen units weekly (HR = 3.1 (95% CI 1.1-8.7)). Multivariate analysis, however, found that only low platelet count was independently associated with HCC (HR = 5.5 (95% CI 0.6-5.1)). CONCLUSIONS: HCC arises in approximately one fifth of indeterminate liver lesions over 4.6 years and is associated with a low platelet count at the time of first diagnosis of an indeterminate lesion. Incidence of HCC was more common in people with viral hepatitis and in those consuming > 14 units of alcohol per week. Our data may be used to support a strategy of enhanced surveillance in patients with indeterminate lesions

F-LSTM: Federated learning-based LSTM framework for cryptocurrency price prediction

In this paper, a distributed machine-learning strategy, i.e., federated learning (FL), is used to enable the artificial intelligence (AI) model to be trained on dispersed data sources. The paper is specifically meant to forecast cryptocurrency prices, where a long short-term memory (LSTM)-based FL network is used. The proposed framework, i.e., F-LSTM utilizes FL, due to which different devices are trained on distributed databases that protect the user privacy. Sensitive data is protected by staying private and secure by sharing only model parameters (weights) with the central server. To assess the effectiveness of F-LSTM, we ran different empirical simulations. Our findings demonstrate that F-LSTM outperforms conventional approaches and machine learning techniques by achieving a loss minimal of $2.3 \times 10^{-4}$. Furthermore, the F-LSTM uses substantially less memory and roughly half the CPU compared to a solely centralized approach. In comparison to a centralized model, the F-LSTM requires significantly less time for training and computing. The use of both FL and LSTM networks is responsible for the higher performance of our suggested model (F-LSTM). In terms of data privacy and accuracy, F-LSTM addresses the shortcomings of conventional approaches and machine learning models, and it has the potential to transform the field of cryptocurrency price prediction

Blockchain-based secure and intelligent data dissemination framework for UAVs in battlefield applications

The modern warfare scenario has immense challenges that can risk personnel's lives, highlighting the need for data acquisition to win a military operation successfully. In this context, unmanned aerial vehicles (UAVs) play a significant role by covertly acquiring reconnaissance data from an enemy location to make the friendly troops aware. The acquired data is mission-critical and needs to be secured from the intruders, which can implicitly manipulate it for their benefit. Moreover, UAVs collect a large amount of data, including high-definition images and surveillance videos; handling such a massive amount of data is a bottleneck on traditional communication networks. To mitigate these issues, this article proposes a blockchain and machine learning (ML)-based secure and intelligent UAV communication underlying sixth-generation (6G) networks, that is, Block-USB. The proposed system refrain the disclosure of highly-sensitive military operations from intruders (either a rogue UAV or a malicious controller). The proposed system uses off-chain storage, that is, Interplanetary file system (IPFS), to improve the blockchain storage capacity. We also present a case study on securing UAV-based military operations by considering multiple scenarios considering controller/UAV malicious. The performance of the proposed system outperforms the traditional baseline 4G/5G and non IPFS-based systems in terms of classification accuracy, communication latency, and data scalability

Anzeige der von den Lehrern des Collegii Carolini in dem Winterhalbjahre von Michaelis 1857 bis Ostern 1858 zu haltenden Vorlesungen und anzustellenden Uebungen

BACKGROUND: The identification of patients with advanced liver fibrosis secondary to non-alcoholic fatty liver disease (NAFLD) remains challenging. Using non-invasive liver fibrosis tests (NILT) in primary care may permit earlier detection of patients with clinically significant disease for specialist review, and reduce unnecessary referral of patients with mild disease. We constructed an analytical model to assess the clinical and cost differentials of such strategies.METHODS: A probabilistic decisional model simulated a cohort of 1000 NAFLD patients over 1 year from a healthcare payer perspective. Simulations compared standard care (SC) (scenario 1) to: Scenario 2: FIB-4 for all patients followed by Enhanced Liver Fibrosis (ELF) test for patients with indeterminate FIB-4 results; Scenario 3: FIB-4 followed by fibroscan for indeterminate FIB-4; Scenario 4: ELF alone; and Scenario 5: fibroscan alone. Model estimates were derived from the published literature. The primary outcome was cost per case of advanced fibrosis detected.RESULTS: Introduction of NILT increased detection of advanced fibrosis over 1 year by 114, 118, 129 and 137% compared to SC in scenarios 2, 3, 4 and 5 respectively with reduction in unnecessary referrals by 85, 78, 71 and 42% respectively. The cost per case of advanced fibrosis (METAVIR ≥F3) detected was £25,543, £8932, £9083, £9487 and £10,351 in scenarios 1, 2, 3, 4 and 5 respectively. Total budget spend was reduced by 25.2, 22.7, 15.1 and 4.0% in Scenarios 2, 3, 4 and 5 compared to £670 K at baseline.CONCLUSION: Our analyses suggest that the use of NILT in primary care can increases early detection of advanced liver fibrosis and reduce unnecessary referral of patients with mild disease and is cost efficient. Adopting a two-tier approach improves resource utilization.</p

The third signal cytokine IL-12 rescues the anti-viral function of exhausted HBV-specific CD8 T cells.

Optimal immune activation of naïve CD8 T cells requires signal 1 mediated by the T cell receptor, signal 2 mediated by co-stimulation and signal 3 provided by pro-inflammatory cytokines. However, the potential for signal 3 cytokines to rescue anti-viral responses in functionally exhausted T cells has not been defined. We investigated the effect of using third signal cytokines IL-12 or IFN-α to rescue the exhausted CD8 T cell response characteristic of patients persistently infected with hepatitis B virus (HBV). We found that IL-12, but not IFN-α, potently augmented the capacity of HBV-specific CD8 T cells to produce effector cytokines upon stimulation by cognate antigen. Functional recovery mediated by IL-12 was accompanied by down-modulation of the hallmark inhibitory receptor PD-1 and an increase in the transcription factor T-bet. PD-1 down-regulation was observed in HBV but not CMV-specific T cells, in line with our finding that the highly functional CMV response was not further enhanced by IL-12. IL-12 enhanced a number of characteristics of HBV-specific T cells important for viral control: cytotoxicity, polyfunctionality and multispecificity. Furthermore, IL-12 significantly decreased the pro-apoptotic molecule Bim, which is capable of mediating premature attrition of HBV-specific CD8 T cells. Combining IL-12 with blockade of the PD-1 pathway further increased CD8 functionality in the majority of patients. These data provide new insights into the distinct signalling requirements of exhausted T cells and the potential to recover responses optimised to control persistent viral infections

Granulocyte colony-stimulating factor as a novel adjunct to improve hepatitis B vaccination

Hepatitis B vaccination is successful in 95% of individuals. In the remainder, despite repeated attempts, immunization often remains unsuccessful. 'Non-response' leaves the individual susceptible to infection. Various strategies have been employed to overcome this. These include the use of adjuncts alongside conventional vaccines which activate immune responses. In this case report we demonstrate the successful use of the hematopoietic growth factor Granulocyte colony-stimulating factor (G-CSF) as a vaccine adjunct in an individual who had previously failed conventional vaccination three times. The patient tolerated the regimen without any side effects and achieved a hepatitis B surface antibody titer greater than 100 IU/L. Use of G-CSF as a vaccine adjunct for hepatitis B has not previously been reported and the outcome in this case suggests that the use of G-CSF in this context warrants further exploration