Multiscale quantification of morphological heterogeneity with creation of a predictor of longer survival in glioblastoma

Intratumor heterogeneity is a main cause of the dismal prognosis of glioblastoma (GBM). Yet, there remains a lack of a uniform assessment of the degree of heterogeneity. With a multiscale approach, we addressed the hypothesis that intratumor heterogeneity exists on different levels comprising traditional regional analyses, but also innovative methods including computer-assisted analysis of tumor morphology combined with epigenomic data. With this aim, 157 biopsies of 37 patients with therapy-naive IDH-wildtype GBM were analyzed regarding the intratumor variance of protein expression of glial marker GFAP, microglia marker Iba1 and proliferation marker Mib1. Hematoxylin and eosin stained slides were evaluated for tumor vascularization. For the estimation of pixel intensity and nuclear profiling, automated analysis was used. Additionally, DNA methylation profiling was conducted separately for the single biopsies. Scoring systems were established to integrate several parameters into one score for the four examined modalities of heterogeneity (regional, cellular, pixel-level and epigenomic). As a result, we could show that heterogeneity was detected in all four modalities. Furthermore, for the regional, cellular and epigenomic level, we confirmed the results of earlier studies stating that a higher degree of heterogeneity is associated with poorer overall survival. To integrate all modalities into one score, we designed a predictor of longer survival, which showed a highly significant separation regarding the OS. In conclusion, multiscale intratumor heterogeneity exists in glioblastoma and its degree has an impact on overall survival. In future studies, the implementation of a broadly feasible heterogeneity index should be considered.     

Worry as a mechanism of the relationship between perceived new knowledge and discouragement to smoke elicited from graphic cigarette warnings

Journal of Behavioral Medicine - Evidence supports the use of graphic warnings to educate the public about the health harms of smoking and suggests warnings eliciting negative emotional responses...     

Experimental study on the biocompatibility and osteogenesis induction ability of PLLA/DDM scaffolds

Odontology - To investigate the characterization and function of a novel porous osteogenic material (PLLA / DDM) containing polylactic acid and demineralized dentin matrix. The surface morphology...     

Dry eye in chronic stroke patients with hemiplegia: A cross-sectional study

ABSTRACT

Objective: Dry eye is reported to be associated with several neurological diseases. The aim of this study is to evaluate the patients with hemiplegia after stroke for dry eye and compare their results with a control group.

Materials and methods: Forty-five patients with hemiplegia and 45 individuals as the control group were included in the study. Tear function tests (Schirmer and tear breakup time) and a dry eye questionnaire for dry eye symptoms (ocular surface disease index) were performed and the results of the two groups were compared.

Results: Schirmer test results were significantly lower in the post-stroke hemiplegia group compared to the control group (11.3 ± 8.2 mm and 20.6 ± 11.6 mm, respectively, p < .001). Tear breakup time results were significantly lower in the post-stroke hemiplegia group compared to the control group (7.9 ± 3.1 s and 12.1 ± 4.3 s, respectively, p < .001). Ocular surface disease index scores were not significantly different between hemiplegia and control groups (21.6 ± 20.0 and 19.8 ± 13.9, respectively, p = .635). Schirmer scores lower than 10 mm (60% and 30%, p < .001) and tear breakup time results lower than 10 s (65.6% and 28.9%, p < .001) were also higher in the hemiplegia group compared to control group.

Conclusion: We found lower Schirmer test and tear breakup time results and similar OSDI scores in hemiplegia patients compared to controls. Hemiplegia patients may have dry eye without typical symptoms. This should be taken into consideration in the follow-up and rehabilitation of post-stroke hemiplegia patients.     

论当前疾病预防控制体系面临的主要问题

对当前的疾病预防控制体系和机构面临的体系不健全、政府投入不充分、事业发展不平衡、人才缺失和能力不足、缺乏系统的理论指导、体系的碎片化严重、与社会经济发展的战略衔接不力、机构内部内生动力和活力不足以及体系治理能力不足等问题做了讨论分析,以期进一步分析在健康中国战略和事业单位机构改革等宏观环境变化所带来的机遇以及疾控体系的发展策略和具体措施,促进疾病预防控制事业在改革中谋发展。     

Predefined vs data-guided training prescription based on autonomic nervous system variation: A systematic review

Monitoring variations in the functioning of the autonomic nervous system may help personalize training of runners and provide more pronounced physiological adaptations and performance improvements. We systematically reviewed the scientific literature comparing physiological adaptations and/or improvements in performance following training based on responses of the autonomic nervous system (ie, changes in heart rate variability) and predefined training. PubMed, SPORTDiscus, and Web of Science were searched systematically in July 2019. Keywords related to endurance, running, autonomic nervous system, and training. Studies were included if they (a) involved interventions consisting predominantly of running training; (b) lasted at least 3 weeks; (c) reported pre- and post-intervention assessment of running performance and/or physiological parameters; (d) included an experimental group performing training adjusted continuously on the basis of alterations in HRV and a control group; and (e) involved healthy runners. Five studies involving six interventions and 166 participants fulfilled our inclusion criteria. Four HRV-based interventions reduced the amount of moderate- and/or high-intensity training significantly. In five interventions, improvements in performance parameters (3000 m, 5000 m, Loadmax, Tlim) were more pronounced following HRV-based training. Peak oxygen uptake () and submaximal running parameters (eg, LT1, LT2) improved following both HRV-based and predefined training, with no clear difference in the extent of improvement in . Submaximal running parameters tended to improve more following HRV-based training. Research findings to date have been limited and inconsistent. Both HRV-based and predefined training improve running performance and certain submaximal physiological adaptations, with effects of the former training tending to be greater.     

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.