Comparison between a new platelet count drop method PL-11, light transmission aggregometry,VerifyNow aspirin system and thromboelastography for monitoring short-term aspirin effects in healthy individuals

Platelet function has been described by many laboratory assays, and PL-11 is a new point-of-care platelet function analyzer based on platelet count drop method, which counts platelet before and after the addition of agonists in the citrated whole blood samples. The present study sought to compare PL-11 with other three major more established assays, light transmission aggregometry (LTA), VerifyNow? aspirin system and thromboelastography (TEG), for monitoring the short-term aspirin responses in healthy individuals. Ten healthy young men took 100?mg/d aspirin for 3-day treatment. Platelet function was measured via PL-11, LTA, VerifyNow and TEG, respectively. The blood samples were collected at baseline, 2 hour, 1 day during the aspirin treatment and 1 day, 5?±?1 days, 8?±?1 days after the aspirin withdrawal. Moreover, 90 additional healthy subjects were recruited to establish a reference range for PL-11. Platelet function of healthy subjects decreased significantly 2 hours after 100?mg/d aspirin intake and began to recover during 4–6 days after the aspirin withdrawal. Correlations between methods were PL-11 vs. LTA (r?=?0.614, p?<?0.01); PL-11 vs. VerifyNow (r?=?0.829, p?<?0.01); PL-11 vs. TEG (r?=?0.697, p?<?0.001). There was no significant bias between PL-11 and LTA at baseline (bias?=?1.94%, p?=?0.804) using Bland-Altman analysis, while the data of PL-11 were significantly higher than LTA (bias?=?24.02%, p?<?0.001) during the aspirin therapy. The reference range for PL-11 in healthy young individuals was from 66.8 to 90.5% (95%CI). When aspirin low-responsiveness was defined as LTA?>?20%, the cut-off values for each method were, respectively: PL-11?>?50%, VerifyNow?>?533 ARU, TEG?>?60.2%. The results of different platelet function assays were uninterchangeable for monitoring aspirin response and correlations among them were also varied. Correlations among PL-11 and other three major assays suggested the ability of PL-11 to assess the treatment effects of aspirin. But a large cohort study is needed to confirm the cut-off value of aspirin response detected by PL-11.     

经自然腔道取标本手术在结直肠外科手术中的应用进展

随着腔镜技术的进一步发展以及微创理念应用于结直肠外科疾病的诊治中,结直肠相关疾病的诊治发生了翻天覆地的变化。由传统的经腹手术到腹腔镜手术、经自然腔道手术,再到经自然腔道取标本手术(NOSES),结直肠疾病的外科诊治在微创领域取得了巨大成果。NOSES技术是目前结直肠外科在微创领域前沿的手术方式之一,它通过经直肠、阴道取标本来避免了腹壁的辅助取标本切口,从而将结直肠外科手术进一步微创化。NOSES技术集传统腹腔镜手术的优势与现代微创外科的理念于一体,它在确保手术效果的基础上集中体现了微创、加速康复外科、功能外科、"无疤"等理念的特点。本文主要就国内外各中心开展NOSES技术在结直肠外科诊治开展中的相关经验、心得和体会进行综述。     

Influence of Fine Grains on the Bending Fatigue Behavior of Two Implant Titanium Alloys

By means of the ultrasonic surface impact (amplitude of 30 μm, strike number of 48,000 times/mm²), nanograins have been achieved in the surfaces of both Ti6Al4V(TC4) and Ti3Zr2Sn3Mo25Nb(TLM) titanium alloys, mainly because of the dislocation motion. Many mechanical properties are improved, such as hardness, residual stress, and roughness. The rotating–bending fatigue limits of TC4 and TLM subjected to ultrasonic impact are improved by 13.1% and 23.7%, separately. Because of the bending fatigue behavior, which is sensitive to the surface condition, cracks usually initiate from the surface defects under high stress amplitude. By means of an ultrasonic impact tip with the size of 8 mm, most of the inner cracks present at the zone with a depth range of 100~250 μm in the high life region. The inner crack core to TC4 usually appears as a deformed long and narrow α-phase, while the cracks in TLM specimens prefer to initiate at the triple grain boundary junctions. This zone crosses the grain refined layer and the deformed coarse grain layer. With the gradient change of elastic parameters, the model shows an increase of normal stress at this zone. Combined with the loss of plasticity and toughness, it is easy to understand these fatigue behaviors.     

Quantile regression and empirical likelihood for the analysis of longitudinal data with monotone missing responses due to dropout,with applications to quality of life measurements from clinical trials

The analysis of quality of life (QoL) data can be challenging due to the skewness of responses and the presence of missing data. In this paper, we propose a new weighted quantile regression method for estimating the conditional quantiles of QoL data with responses missing at random. The proposed method makes use of the correlation information within the same subject from an auxiliary mean regression model to enhance the estimation efficiency and takes into account of missing data mechanism. The asymptotic properties of the proposed estimator have been studied and simulations are also conducted to evaluate the performance of the proposed estimator. The proposed method has also been applied to the analysis of the QoL data from a clinical trial on early breast cancer, which motivated this study.