Biomechanical behavior of brain injury caused by sticks using finite element model and Hybrid-III testing

Objective: To study the biomechanical mechanism of head injuries beaten with sticks, which is common in the battery or assaultive cases. Methods: In this study, the Hybrid-III anthropomorphic test device and finite element model (FEM) of the total human model for safety (THUMS) head were used to determine the biomechanical response of head while being beaten with different sticks. Total eight Hybrid-III tests and four finite element simulations were conducted. The contact force, resultant acceleration of head center of gravity, intracranial pressure and von Mises stress were calculated to determine the different biomechanical behavior of head with beaten by different sticks. Results: In Hybrid-III tests, the stick in each group demonstrated the similar kinematic behavior under the same loading condition. The peak values of the resultant acceleration for thick iron stick group, thin iron stick group, thick wooden stick group and thin wooden stick group were 203.4 g, 221.1 g, 170.5 g and 122.2 g respectively. In finite element simulations, positive intracranial pressure was initially observed in the frontal comparing with negative intracranial pressure in the contra-coup site. Subsequently the intracranial pressure in the coup site was decreasing toward negative value while the contra-coup intracranial pressure increasing toward positive values. Conclusions: The results illustrated that the stiffer and larger the stick was, the higher the von Mises stress, contact force and intracranial pressure were. We believed that the results in the Hybrid-III tests and THUMS head simulations for brain injury beaten with sticks could be reliable and useful for better understanding the injury mechanism.     

Poly(ortho ester) nanoparticles targeted for chronic intraocular diseases: ocular safety and localization after intravitreal injection

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.     

Unexpected Return for Follow-up During the First Year of Multidisciplinary Care May Be Predictive of Rapid Deterioration of Renal Function

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.     

Craving-induced effects of different drug cues on persons abstaining from heroin

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.     

外泌体在肿瘤转移前微环境形成中的作用

肿瘤的转移前微环境（pre-metastatic niche，PMN）特指原发肿瘤灶为肿瘤细胞远处播散和定植准备的微环境，此微环境的六个特征包括炎症、免疫抑制、血管生成/血管通透性、亲器官性、重编程和淋巴管生成。PMN形成的关键成分包括肿瘤源性分泌因子、细胞外囊泡（含外泌体）、骨髓源性细胞、免疫抑制细胞和宿主基质细胞等，其中，外泌体作为细胞间重要的信使，在肿瘤PMN的形成中具有重要作用。本综述就外泌体在肿瘤PMN形成中的作用进行探讨。     

Rethinking PICO in the Machine Learning Era: ML-PICO

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.