Laparoscopic vs open hepatectomy for hepatocellular carcinoma in patients with cirrhosis: a meta-analysis of the long-term survival outcomes

Background In patients with hepatocellular carcinoma (HCC) and cirrhosis, laparoscopic hepatectomy (LH) confers short-term benefits over open hepatectomy (OH) but the long-term outcomes of this procedure are unclear. This systematic review aims to compare the long-term survival outcomes of LH and OH for patients with HCC and underlying cirrhosis. Methods EMBASE, MEDLINE and Scopus databases were searched from date of inception to 7th October 2016. Controlled clinical studies comparing LH to OH for HCC in cirrhotic patients, which reported long-term overall and disease-free survival were included. The studies were evaluated using the MOOSE guidelines and Newcastle-Ottawa Scale. Data were extracted and analysed using a fixed-effects model. Results Five non-randomised, retrospective observational studies representing 888 patients were included. LH was associated with significantly lower tumour recurrence [OR: 0.65, 95% CI: 0.48, 0.89]. LH conferred greater overall survival at 1- [HR: 0.41, 95% CI: 0.25, 0.68], 3- [HR: 0.63, 95% CI: 0.46, 0.87] and 5-years [HR: 0.60, 95% CI: 0.45, 0.80]. With LH, there was higher disease-free survival at 1-year [HR: 0.71, 95% CI: 0.53, 0.96], but not at 3- [HR: 0.89, 95% CI: 0.70, 1.14]; and 5-years [HR: 0.85, 95% CI: 0.70, 1.04]. Conclusions Laparoscopic surgery is associated with comparable postoperative and survival outcomes in patients with HCC and underlying cirrhosis. With careful selection of patients, this approach is safe, feasible and advantageous

The role of joint distraction in the treatment of knee osteoarthritis: a systematic review and quantitative analysis

Introduction: Knee osteoarthritis is a major cause of pain and disability for which joint distraction is a potential treatment to delay the need for knee arthroplasty. This systematic review aims to assess the short- and long-term clinical and structural outcomes following knee joint distraction (KJD). Methods: MEDLINE, EMBASE, Scopus and Web of Science databases were searched from the date of inception to 26th June 2019. Clinical studies investigating joint distraction for knee osteoarthritis with outcomes including ∆WOMAC index, ∆VAS pain score and ∆joint space width were included. The review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) – CRD42018087032. Results: Nine studies comprising a total of 507 patients were included. There were four randomised controlled trials (RCTs), five open prospective cohort studies and one case series. Overall, there were significant improvements in WOMAC index, VAS pain score and joint space width following KJD, which persisted up till nine years. KJD also demonstrated comparable clinical outcomes with HTO and TKA. Conclusion: There is moderate quality evidence supporting the beneficial outcomes of joint distraction for knee osteoarthritis. Larger RCTs with longer follow-up (>1 year) are necessary to establish the true effect size of this procedure

Economics of neuraminidase inhibitor stock piling for pandemic influenza, Singapore.

We compared strategies for stock piling neuraminidase inhibitors to treat and prevent influenza in Singapore. Cost-benefit and cost-effectiveness analyses, with Monte Carlo simulations, were used to determine economic outcomes. A pandemic in a population of 4.2 million would result in an estimated 525-1,775 deaths, 10,700-38,600 hospitalization days, and economic costs of 0.7 dollars to 2.2 billion Singapore dollars. The treatment-only strategy had optimal economic benefits: stock piles of antiviral agents for 40% of the population would save an estimated 418 lives and 414 million dollars, at a cost of 52.6 million dollars per shelf-life cycle of the stock pile. Prophylaxis was economically beneficial in high-risk subpopulations, which account for 78% of deaths, and in pandemics in which the death rate was >0.6%. Prophylaxis for pandemics with a 5% case-fatality rate would save 50,000 lives and 81 billion dollars. These models can help policymakers weigh the options for pandemic planning

Joint distraction for knee osteoarthritis: protocol for a systematic review and meta-analysis

Background Osteoarthritis is a degenerative joint disease that is highly prevalent worldwide. Knee osteoarthritis is the most common form of osteoarthritis and is a major cause of pain and disability. However, there remains a lack of treatments available that have demonstrated effectiveness in stopping or reversing the degenerative process. Joint distraction has emerged as a viable alternative in the treatment of knee osteoarthritis to delay the need for knee arthroplasty. Methods An electronic search will be conducted on MEDLINE, EMBASE, Web of Science, CINAHL, Cochrane and EBSCO databases. Clinical studies investigating joint distraction for knee osteoarthritis, which reported clinical or structural outcomes including ∆WOMAC index, ∆VAS pain score and ∆joint space width will be included. Risk of bias will be assessed using the Newcastle-Ottawa Scale for observational studies and Cochrane Collaboration tool for randomised controlled trials. Quality of studies will be assessed using the modified Coleman methodology score. Discussion This systematic review will summarise the short- and long-term clinical and structural outcomes following joint distraction for knee osteoarthritis. The findings from this review will establish the quality of currently available evidence, which will determine the need for further studies to establish the true effect size of this procedure

Learning activation functions from data using cubic spline interpolation

Neural networks require a careful design in order to perform properly on a given task. In particular, selecting a good activation function (possibly in a data-dependent fashion) is a crucial step, which remains an open problem in the research community. Despite a large amount of investigations, most current implementations simply select one fixed function from a small set of candidates, which is not adapted during training, and is shared among all neurons throughout the different layers. However, neither two of these assumptions can be supposed optimal in practice. In this paper, we present a principled way to have data-dependent adaptation of the activation functions, which is performed independently for each neuron. This is achieved by leveraging over past and present advances on cubic spline interpolation, allowing for local adaptation of the functions around their regions of use. The resulting algorithm is relatively cheap to implement, and overfitting is counterbalanced by the inclusion of a novel damping criterion, which penalizes unwanted oscillations from a predefined shape. Experimental results validate the proposal over two well-known benchmarks.Comment: Submitted to the 27th Italian Workshop on Neural Networks (WIRN 2017

Proton Decay in a Minimal SUSY SO(10) Model for Neutrino Mixings

A minimal renormalizable SUSY SO(10) model with B-L symmetry broken by {\bf 126} Higgs field has recently been shown to predict all neutrino mixings and the ratio $\Delta m^2_{\odot}/\Delta m^2_A$ in agreement with observations. Unlike models where B-L is broken by {\bf 16} Higgs, this model guarantees automatic R-parity conservation and hence a stable dark matter as well as the absence of dim=4 baryon violating operator without any additional symmetry assumptions. In this paper, we discuss the predictions of the model for proton decay induced at the GUT scale. We scan over the parameter space of the model allowed by neutrino data and find upper bounds on the partial lifetime for the modes $\tau(n\to \pi^0\bar{\nu})=~2\tau(p\to \pi^+\bar{\nu})\leq (5.7-13)\times 10^{32}$ yrs and $\tau(n\to K^0\bar{\nu})\leq 2.97\times 10^{33}$ yrs for the average squark mass of a TeV and wino mass of 200 GeV, when the parameters satisfy the present lower limits on $\tau(p\to K^+\bar{\nu})$ mode. These results can be used to test the model.Comment: 17 pages, 6 figures; Minor corrections with improved predictions; references update

Probing the Majorana nature of TeV-scale radiative seesaw models at collider experiments

A general feature of TeV-scale radiative seesaw models, in which tiny neutrino masses are generated via loop corrections, is an extended scalar (Higgs) sector. Another feature is the Majorana nature; e.g., introducing right-handed neutrinos with TeV-scale Majorana masses under the discrete symmetry, or otherwise introducing some lepton number violating interactions in the scalar sector. We study phenomenological aspects of these models at collider experiments. We find that, while properties of the extended Higgs sector of these models can be explored to some extent, the Majorana nature of the models can also be tested directly at the International Linear Collider via the electron-positron and electron-electron collision experiments.Comment: 19 pages, 7 figures, version published in Physics Letters

Clinical utility of exercise training in heart failure with reduced and preserved ejection fraction

Reduced exercise tolerance is an independent predictor of hospital readmission and mortality in patients with heart failure (HF). Exercise training for HF patients is well established as an adjunct therapy, and there is sufficient evidence to support the favorable role of exercise training programs for HF patients over and above the optimal medical therapy. Some of the documented benefits include improved functional capacity, quality of life (QoL), fatigue, and dyspnea. Major trials to assess exercise training in HF have, however, focused on heart failure with reduced ejection fraction (HFREF). At least half of the patients presenting with HF have heart failure with preserved ejection fraction (HFPEF) and experience similar symptoms of exercise intolerance, dyspnea, and early fatigue, and similar mortality risk and rehospitalization rates. The role of exercise training in the management of HFPEF remains less clear. This article provides a brief overview of pathophysiology of reduced exercise tolerance in HFREF and heart failure with preserved ejection fraction (HFPEF), and summarizes the evidence and mechanisms by which exercise training can improve symptoms and HF. Clinical and practical aspects of exercise training prescription are also discussed

What do we learn from correlations of local and global network properties?

In complex networks a common task is to identify the most important or "central" nodes. There are several definitions, often called centrality measures, which often lead to different results. Here we study extensively correlations between four local and global measures namely the degree, the shortest-path-betweenness, the random-walk betweenness and the subgraph centrality on different random-network models like Erdos-Renyi, Small-World and Barabasi-Albert as well as on different real networks like metabolic pathways, social collaborations and computer networks. Correlations are quite different between the real networks and the model networks questioning whether the models really reflect all important properties of the real world