Treatment of posterior eye diseases is more challenging than the anterior segment ailments due to a series of anatomical barriers and physiological constraints confronted by drug delivery to the back of the eye. In recent years, concerted efforts in drug delivery have been made to prolong the residence time of drugs injected in the vitreous humor of the eye. Our previous studies demonstrated that poly(ortho ester) (POE) nanoparticles were biodegradable/biocompatible and were capable of long-term sustained release. The objective of the present study was to investigate the safety and localization of POE nanoparticles in New Zealand white rabbits and C57BL/6 mice after intravitreal administration for the treatment of chronic posterior ocular diseases. Two concentration levels of POE nanoparticles solution were chosen for intravitreal injection: 1.5?mg/ml and 10?mg/ml. Our results demonstrate that POE nanoparticles were distributed throughout the vitreous cavity by optical coherence tomography (OCT) examination 14 days post-intravitreal injection. Intraocular pressure was not changed from baseline. Inflammatory or adverse effects were undetectable by slit lamp biomicroscopy. Furthermore, we demonstrate that POE nanoparticles have negligible toxicity assessed at the cellular level evidenced by a lack of glia activation or apoptosis estimation after intravitreal injection. Collectively, POE nanoparticles are a novel and nontoxic as an ocular drug delivery system for the treatment of posterior ocular diseases. 相似文献
Multidisciplinary predialysis education and team care (MDC) may slow the decline in renal function in patients with chronic kidney disease (CKD). However, associations between unexpected return during MDC and progression of renal dysfunction have not been characterized in patients with CKD. Our study aimed to determine the association between exacerbation of renal dysfunction and the frequency of unexpected return during follow-up.A total of 437 patients with CKD receiving multidisciplinary care between January 2009 and June 2013 at the Shin-Kong Wu Ho-Su Memorial Hospital were included in this retrospective observational cohort study, and multiple imputations were performed for missing data. The predictor was the frequency of unexpected return for follow-up during the first year after entering MDC. Main outcome was monthly declines in estimated glomerular filtration rates (eGFR). Moreover, the demographic data, comorbidities, history of medication, and routine laboratory data for patients with CKD were collected.Among all patients, 59.7% were male, the mean age at initiation of MDC was 69.4 ± 13.2 years, and the duration of follow-up was 21.4 ± 3.3 months. The subjects were divided into 2 groups according to frequencies of follow-up (≤4 and > 4 visits) during the 1st year of MDC. The patients with CKD were regularly followed up every 3 months as a part of MDC in our hospital, and patients who returned for more than 4 follow-up visits were included in the unexpected return group. In crude regression analyses, unexpected return was significantly associated with higher monthly declines of eGFR (β = 0.092, 95% confidence interval, 0.014–0.170). This association remained after adjustments for multiple variables, and subgroup analyses of unexpected return showed that male gender, older age, CKD stage 1 to 3, hypertension, history of coronary artery disease, and use of renin–angiotensin system blockade were significantly associated with declines in renal function.In conclusion, unexpected return for follow-up during the 1st year of MDC was significantly associated with the deterioration of renal function. 相似文献
目的探讨8周基础军训(basic military training,BMT)对入伍新兵血像中红细胞及其相关指标的影响,为指导科学的军事训练提供参考。方法数据来自新疆边防部队2015年度入伍的50名男性新兵,分别在BMT前后测定并记录受试新兵的红细胞计数、血红蛋白浓度及血清铁蛋白等。结果经过8周的BMT,新兵血液中血红蛋白浓度、红细胞计数及血清铁蛋白均显著下降(P0.05,P0.01)。结论 8周BMT可能导致入伍新兵发生运动性贫血,铁缺乏可能是其主要原因。 相似文献
Background: The key factors of inducing drug cravings in persons abstaining from drug use remain a focus of addictions research. Given the accumulating evidences, the scope of cues investigated in the cue-reactivity paradigm has increased considerably. Yet, few studies have examined the effects of the intensity and endurance of different types of cues on their ability to induce craving. This study investigated differences among drug-cue words, negative physiological-cue words, and negative social-cue words in the induction of drug cravings among persons abstaining from heroin.
Methods: The sample consisted of 149 male abstinent heroin abusers from four addiction rehabilitation centers in China. Based on their abstinence lengths, they were labeled as short-term, medium-term, and long-term abstainer participants respectively. All participants completed a stress-imagery task and rated craving by visual analog scale.
Results: There was a significant interaction of cue type and abstinence length. There was no difference on the craving induced by three types of cue words in the short-term group. In the medium-term group, craving induced by negative social-cue words was significantly stronger than that by negative physiological-cue words, but not that by drug-cue words. In the long-term group, the craving induced by negative social-cue words remained the strongest, significantly stronger than that by both drug-cue words and negative physiological-cue words.
Conclusion: Negative social-cue words presented in the current study retain the ability to induce craving in heroin abstainers; this finding suggests that negative social cues encountered under more general circumstances could be a risk factor for relapse. 相似文献
Background Machine learning (ML) has captured the attention of many clinicians who may not have formal training in this area but are otherwise increasingly exposed to ML literature that may be relevant to their clinical specialties. ML papers that follow an outcomes-based research format can be assessed using clinical research appraisal frameworks such as PICO (Population, Intervention, Comparison, Outcome). However, the PICO frameworks strain when applied to ML papers that create new ML models, which are akin to diagnostic tests. There is a need for a new framework to help assess such papers. Objective We propose a new framework to help clinicians systematically read and evaluate medical ML papers whose aim is to create a new ML model: ML-PICO (Machine Learning, Population, Identification, Crosscheck, Outcomes). We describe how the ML-PICO framework can be applied toward appraising literature describing ML models for health care. Conclusion The relevance of ML to practitioners of clinical medicine is steadily increasing with a growing body of literature. Therefore, it is increasingly important for clinicians to be familiar with how to assess and best utilize these tools. In this paper we have described a practical framework on how to read ML papers that create a new ML model (or diagnostic test): ML-PICO. We hope that this can be used by clinicians to better evaluate the quality and utility of ML papers. 相似文献