The value of 18F-fluorodeoxyglucose positron emission tomography for prediction of treatment response in gastrointestinal stromal tumors: a systematic review and metaanalysis

Background: Early detection of response to treatment is critically important in gastrointestinal stromal tumors (GIST). Therefore, the present systematic review and meta-analysis assessed the value of 18f-fluorodeoxyglucose positron emission tomography (18FDG– PET) on prediction of therapeutic response of GIST patients to systemic treatments. Methods: The literature search was conducted using PubMed, SCOPUS, Cochrane, and Google Scholar databases, and review article references. Eligible articles were defined as studies included confirmed GIST patients who underwent 18FDG–PET as well as assessing the screening role of it. Results: Finally, 21 relevant articles were included. The analysis showed the pooled sensitivity and specificity of 18FDG–PET in evaluation of response to treatment of GIST patient were 0.90 (95% CI: 0.85–0.94; I 2 = 52.59, P = 0.001) and 0.62 (95% CI: 0.49–0.75; I 2 = 69.7, P = 0.001), respectively. In addition, the pooled prognostic odds ratio of 18FDG–PET for was 14.99 (95% CI, 6.42–34.99; I 2 = 100.0, P < 0.001). The Meta regression showed that sensitivity of 18FDG-PET was higher if the sample size of study was equal or more than 30 cases (sensitivity = 0.93; 95% CI: 0.89–0.97), when using PET/CT (sensitivity = 0.92; 95% CI: 0.89–0.97), and self-design criteria (sensitivity = 0.93; 95% CI: 0.87–1.0). Conclusion: The present meta-analysis showed 18FDG–PET has a significant value in predicting treatment response in GIST patients

EVALUATION OF HYPOGLYCEMIC AND HYPOLIPIDEMIC EFFECTS OF INTERNAL SEPTUM OF WALNUT FRUIT IN ALLOXAN-INDUCED DIABETIC RATS

Background: Todays, the popularity of herbal medicine is increasing worldwide. Due to importance the evaluation of medicinal herbs efficacy and safety, the present study was conducted to investigate the antidiabetic and hypolipidemic effects of internal septum of walnut fruit (ISWF) ethanolic extract in diabetic rats. Materials and methods: Alloxan diabetic rats treated orally with ethanolic extract of ISWF (0-400mg/kg) for 28 days. To evaluate its anti-diabetic activity, the animals fasting blood glucose were determined on the first, 14th and 29th days. Moreover, oral glucose tolerance test (OGTT) was performed in diabetic rats at the last day of the study. After 24h of last administration, the blood samples were collected, and the Plasma lipids and liver enzymes levels were measured in fasting overnight rats. Results: The extract significantly decreased blood glucose (

Role of Long Non-Coding RNAs in Conferring Resistance in Tumors of the Nervous System

Tumors of the nervous system can be originated from several locations. They mostly have high mortality and morbidity rate. The emergence of resistance to chemotherapeutic agents is a hurdle in the treatment of patients. Long non-coding RNAs (lncRNAs) have been shown to influence the response of glioblastoma/glioma and neuroblastoma to chemotherapeutic agents. MALAT1, NEAT1, and H19 are among lncRNAs that affect the response of glioma/glioblastoma to chemotherapy. As well as that, NORAD, SNHG7, and SNHG16 have been shown to be involved in conferring this phenotype in neuroblastoma. Prior identification of expression amounts of certain lncRNAs would help in the better design of therapeutic regimens. In the current manuscript, we summarize the impact of lncRNAs on chemoresistance in glioma/glioblastoma and neuroblastoma

A scattering and repulsive swarm intelligence algorithm for solving global optimization problems

The firefly algorithm (FA), as a metaheuristic search method, is useful for solving diverse optimization problems. However, it is challenging to use FA in tackling high dimensional optimization problems, and the random movement of FA has a high likelihood to be trapped in local optima. In this research, we propose three improved algorithms, i.e., Repulsive Firefly Algorithm (RFA), Scattering Repulsive Firefly Algorithm (SRFA), and Enhanced SRFA (ESRFA), to mitigate the premature convergence problem of the original FA model. RFA adopts a repulsive force strategy to accelerate fireflies (i.e. solutions) to move away from unpromising search regions, in order to reach global optimality in fewer iterations. SRFA employs a scattering mechanism along with the repulsive force strategy to divert weak neighbouring solutions to new search regions, in order to increase global exploration. Motivated by the survival tactics of hawk-moths, ESRFA incorporates a hovering-driven attractiveness operation, an exploration-driven evading mechanism, and a learning scheme based on the historical best experience in the neighbourhood to further enhance SRFA. Standard and CEC2014 benchmark optimization functions are used for evaluation of the proposed FA-based models. The empirical results indicate that ESRFA, SRFA and RFA significantly outperform the original FA model, a number of state-of-the-art FA variants, and other swarm-based algorithms, which include Simulated Annealing, Cuckoo Search, Particle Swarm, Bat Swarm, Dragonfly, and Ant-Lion Optimization, in diverse challenging benchmark functions

From an Organic-Functionalized Ge4S6 Cage to a Chalcogenidometallate Organic Coordination Framework with Antiferromagnetic Chain Behavior

We report the proof of principle for an approach toward a novel type of inorganic-organic hybrid compound. Compound [Mn2{(OOCC2H4Ge)4S6}(MeOH)(dmf)2] is constructed by inorganic cages (Ge4S6) that are linked through terminal COO- donor groups by Mn2+ ions within zigzag chains of corner-sharing [MnO6] units, exhibiting intrachain antiferromagnetic couplin

Drought Forecasting Using Genetic Algorithm and Conjoined Model of Neural Network-Wavelet

Drought is one of the important natural disasters that may happen in any climate conditions. Since drought is inevitable phenomenon, therefore familiar with that natural disaster is very important for reliable water management. Drought prediction system design is one of the efficient ways that it can minimize the drought damages. In this research for predicting the coming drought, genetic algorithm and conjoined model of neural network-wavelet is used for analyzing standardized precipitation index. The results show that genetic algorithm and conjoined model of neural network-wavelet is more satisfactory than genetic algorithm and neural network

Analysis of unsafe behaviors before and after intervention training

Background and aims   Today, the reduction of unsafe work behavior is an accepted principle. Unsafe behaviors at work are said to be the main cause of work accidents. Therefore, careful  attention toward unsafe work behavior is one of the main factors for eliminating the causes of injuries and damages which has been taken into consideration in recent years.Also, due to the high rate of accidents in foundry industries; the present research has been conducted to reduce unsafe  work behaviors through an appropriate method.   Methods   The present study is of analytical; interventional. The subject investigated in this study is one of foundry industries. Sample size was determined. In order to gather data, the methods of observation, interview and checklist were used. The five-year-accident record of the   company was analyzed.Data analysis was done by means of spss10.   Results   In the present study, Pearson Correlation test indicates that there is no relationship  between safety performance score before and after training and the age of workers. (r=0.6 Pvalue=  0.639) Pearson correlation test also demonstrated that there is a linear relationship between  safety performance score and work experience. In other words, the more work experience, the  more safety performance (r=0.25 P-value=0.03). Pearson correlation test indicates that there is  no relationship between safety performance score and educational level. (r=0.12 P-value=0.29)   Conclusion   The present study indicated that with the reduction of unsafe work behavior  accidents declined significantly. This research also resulted in the reduction of unsafe work  behaviors, lost workdays as well as work accidents