Background: Increased uptake of robotic surgery has led to interest in learning curves for robot-assisted procedures. Learning curves, however, are often poorly defined. This systematic review was conducted to identify the available evidence investigating surgeon learning curves in robot-assisted surgery.Methods: MEDLINE, Embase and the Cochrane Library were searched in February 2018, in accordance with PRISMA guidelines, alongside hand searches of key congresses and existing reviews. Eligible articles were those assessing learning curves associated with robot-assisted surgery in patients.Results: Searches identified 2316 records, of which 68 met the eligibility criteria, reporting on 68 unique studies. Of these, 49 assessed learning curves based on patient data across ten surgical specialties. All 49 were observational, largely single-arm (35 of 49, 71 per cent) and included few surgeons. Learning curves exhibited substantial heterogeneity, varying between procedures, studies and metrics. Standards of reporting were generally poor, with only 17 of 49 (35 per cent) quantifying previous experience. Methods used to assess the learning curve were heterogeneous, often lacking statistical validation and using ambiguous terminology.Conclusion: Learning curve estimates were subject to considerable uncertainty. Robust evidence was lacking, owing to limitations in study design, frequent reporting gaps and substantial heterogeneity in the methods used to assess learning curves. The opportunity remains for the establishment of optimal quantitative methods for the assessment of learning curves, to inform surgical training programmes and improve patient outcomes.

BackgroundIn the present era, obesity is increasing rapidly, and high dietary intake of lipid could be a noteworthy risk factor for the occasion of obesity, as well as nonalcoholic fatty liver disease, which is the independent risk factor for type 2 diabetes and cardiovascular disease. For a long time, high-lipid diet (HLD) in “fast food” is turning into part of our everyday life. So, we were interested in fulfilling the paucity of studies by means of preliminary evaluation of these three alternative doses of HLD on a rat model and elucidating the possible mechanism of these effects and divulging the most alarming dose.MethodsThirty-two rats were taken, and of these, 24 were fed with HLD in three distinctive compositions of edible coconut oil and vanaspati ghee in a ratio of 2:3, 3:2 and 1:1 (n = 8), orally through gavage at a dose of 10 mL/kg body weight for a period of 28 days, whereas the other eight were selected to comprise the control group.ResultsAfter completion of the experiment, followed by analysis of data it was revealed that hyperlipidemia with increased liver and cardiac marker enzymes, are associated with hepatocellular injury and cardiac damage. The data also supported increased proinflammatory cytokines such as interleukin 6 (IL-6) and tumor necrosis factor α (TNF-α). As oxidative stress parameter increased in both liver and heart, there is also an increased in TNF-α due to an increased expression of inducible nitric oxide (NO) synthase, which led to a high production of NO. Moreover, HLD treatment explicitly weakens reasonability of hepatocytes and cardiomyocytes conceivably through G0/G1 or S stage capture or perhaps by means of enlistment of sub-G0/G1 DNA fragmentation and a sign of apoptosis.ConclusionsBased on the outcomes, it tends to be inferred that consequences of the present examination uncovered HLD in combination of 2:3 applies most encouraging systemic damage by reactive oxygen species generation and hyperlipidemia and necroapoptosis of the liver and heart. Hence, outcome of this study may help to formulate health care strategy and warns about the food habit in universal population regarding the use of hydrogenated and saturated fats (vanaspati ghee) in diet.

In the context of failure of treatment for non alcoholic fatty liver disease (NAFLD)-mediated systemic damages, recognition of novel and successful characteristic drug to combat these anomalous situations is earnestly required. The present study is aimed to evaluate protective value of ethanol extract of Coccinia grandis leaves (EECGL), naturally occurring medicinal plant, on NAFLD-mediated systemic damage induced by high lipid diet along with monosodium glutamate (HM)-fed rats. Our study uncovered that EECGL significantly ameliorates HM-induced hyperlipidemia, increased lipogenesis and metabolic disturbances (via up regulation of PPAR-α and PPAR-γ), oxidative stress (via reducing the generation of reactive oxygen species and regulating the redox-homeostasis) and inflammatory response (via regulating the pro-inflammatory and anti-inflammatory factors with concomitant down regulation of NF-kB, iNOS, TNF-α and up regulation of eNOS). Furthermore, EECGL significantly inhibited HM-induced increased population of cells in sub G0/G1 phase, decreased Bcl2 expression and thereby loss of mitochondrial membrane potential with over expression of Bax, p53, p21, activation of caspase 3 and 9 indicated the apoptosis and suppression of cell survival. It is perhaps the first comprehensive study with a mechanistic approach which provides a strong unique strategy for the management of HM-induced systemic damage with effective dose of EECGL.

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This paper investigates a change-point estimation problem in the context of high-dimensional Markov random field models. Change-points represent a key feature in many dynamically evolving network structures. The change-point estimate is obtained by maximizing a profile penalized pseudo-likelihood function under a sparsity assumption. We also derive a tight bound for the estimate, up to a logarithmic factor, even in settings where the number of possible edges in the network far exceeds the sample size. The performance of the proposed estimator is evaluated on synthetic data sets and is also used to explore voting patterns in the US Senate in the 1979-2012 period.