Microglial cells are the resident immune cells of brain. The activated microglia produces a range of deleterious substances, which plays an important role in the inflammation of post-stroke, such as superoxide, nitric oxide, matrix metalloproteinases, etc. The activa-tion of microglia may involve triggering receptor expressed on myeloid cells-1, Toll-like receptors 4, peroxisome proliferator-activated re-ceptors, purinergic receptors, etc. Intervention targeted to microglial receptor is becoming a new strategy for ischemic stroke.

A comprehensive review was conducted to evaluate characteristics of the innovative research fund in a military hospital during past five years.We created a special index system according to the features of this innovative research fund:short supporting period,less amount of funding,and strict limit to the pre-study with the combination of common Research Performance Indicators.We use this index system to evaluate all finished projects and scored their performance.Other factors,such as research area,age of researchers,and job title,were also combined to analyze the relationship between funded research performance and fund characteristics.We found that all projects with higher performance score in past 5 years were conducted by young researchers,while this meets our original intention that using this fund to support junior scientists.In addition,we also found that the process of project assessment was fire and scientific,and funding for key research disciplines provided high level research outcomes.

Autophagy plays an important role in the regulation of activation and inflammation of microglia after ischemic stroke. The interaction between autophagy of microglia and the inflammation mediated by microglia after ischemic stroke was complex and a large num-ber of molecules were involved. The receptors of microglia activation and related substances may be possible mechanism in the regulation of microglia autophagy. Autophagy inhibitors and microglia receptor targeting therapy may provide new strategies for the clinical treatment of ischemic stroke. This paper summarized the progress of microglia autophagy after ischemic stroke.

In this study,Polygalae radix and its adulterants were identified by psbA-trnH sequence.The genomic DNA was extracted from forty-six samples, the psbA-trnH sequences were amplified and sequenced Bi-directionally, and then assembled sequences by Codoncode Aligner V 3.7.1. The genetic distances were computed by kimura 2-parameter (K2P) model, and the Neighbor-Joining tree was constructed by MEGA 6.0. Results showed that minimum intra-specific K2P distance of Polygala tenuifolia and Polygala sibirica were 0.004 and 0, which were smaller than the maximum intra-specific K2P. The NJ tree showed Polygalae radix can be distinguished from its adulterants by psbA-trnH sequences. Therefore, using psbA-trnH sequences can distinguish Polygalae radix from its adulterants.

Objective To utilize sophisticated CT-driven radiomics to prognosticate the mutation situation of KRAS in patients with colorectal cancer(CRC).Methods A total of 393 patients who underwent KRAS mutation testing and preoperative triphasic enhanced CT were analyzed retrospectively.All patients were divided into training group(n=276)and validation group(n=117)with a ratio of 7∶3.The characteristics tightly associated with KRAS mutation were extracted and screened to construct three models,include clinical,radiomics,and clinical-radiomics fusion models for prediction of KRAS mutation.The performance and clinical utility of these three models were assessed via receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The study identified significant correlations between KRAS mutation and CEA,CA199,and a set of 13 radiomics features,respective-ly.Based on these clinical indicators and radiomics features,clinical,radiomics,and clinical-radiomics fusion models were constructed to prognosticate KRAS mutation.The radiomics model construc-ted in this study had good performance for the prediction of KRAS mutation status in CRC patients.Most notably,a clinical-radiomics nomogram that amalgamated both clinical risk factors and radiomics parameters emerged as the most effective predictor of KRAS mutation,with an area under the curve(AUC)of 0.782 and 0.744 in the training group and validation group,respectively.Conclusion The refined CT radiomics model serves as a robust,non-invasive,quantitative tool for the assessment of KRAS mutation status in CRC patients.

Both morbidity and mortality of gastric cancer are in the front rank among malignant tumors.At present,enhanced CT is served as an important imaging method for preoperative diagnosis and assessment of gastric cancer,but it is mostly based on morphological evaluation and unable to perform quantitative analysis.The functional imaging technology represented by energy spectral CT and CT perfusion imaging has a variety of quantitative parameters,which is expected to make up for the shortcomings of conventional CT.The review introduces the basic principles of energy spectral CT and CT perfusion imaging,and summarizes their applications in the diagnosis,pathological classification,grading,staging and efficacy prediction of gastric cancer,aiming to improve the understanding of functional CT imaging for the pretreatment assessment in gastric cancer.

Gastrointestinal stromal tumors(GISTs)are the most common mesenchymal tumors of the gastrointestinal tract,and they are also genetically heterogeneous tumors.c-KIT gene or PDGFRA gene mutation is the main driving factor leading to its occurrence,and it is also one of the key factors affecting the treatment and prognosis of patients with GISTs.Imaging examination is non-invasive and can display tumors from multiple angles and directions,making it the main method for preoperative evaluation of GISTs.With the continuous development of imaging technology,non-invasive and definite genotyping of GISTs by imaging methods before surgery plays a positive role in the selection of targeted drugs and doses for patients and the evaluation of targeted treatment efficacy.This article reviews the imaging progress on the genotype of GISTs and the efficacy of targeted therapy.

Objective: Human rhinovirus A21 (HRVA21) with mutations in antigenic gene has been reported causing severe human infections. This study aimed to investigate intensively the pathogenesis of HRVA21 by identifying the characteristics of neutralizing antibodies (NAbs) distribution. Methods: Virus stock was isolated from HRVA21-positive respiratory specimens. The tissue culture infective dose 50 (TCID₅₀) was applied. Sera from healthy volunteers in different age groups were used to analyze the NAbs by using the diluted serum and fixed viral TCID₅₀. Results: We obtained the HRVA21 virus stock and its whole genome sequences shared 100% similarity to the used clinical sample. In the 379 collected serum samples, the positive rates of NAbs were 21.7%, 14.1%, 28.2%, 25.4%, 27.9% and 20.7% in age groups of 0-5 y, 5-14 y, 15-25 y, 26-45 y, 46-60 y and > 60 y, respectively. In age groups of >5-14 y and 15-25 y, the positive rate of NAbs showed significantly different (χ²=4.68454, P=0.03044). Higher geometric mean titers were found in 15-25 y group compared to 5-14 y age groups (P=0.0313). Conclusions The low level of HRVA21 NAbs in different age groups indicated a low epidemic of HRV21 infection and high susceptability to infections by the virus.

Objective: To explore the correlation between microdamage in white matter and radiotherapy dose at early stage after radiotherapy (RT) in patients with nasopharyngeal carcinoma (NPC). Methods: Thirty-three patients who were initially diagnosed with NPC were recruited and received diffusion tensor imaging (DTI) scan and neuro-cognitive scale test within 1 week before RT and the first day after RT. DTI-related characteristic parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ_‖), and radial diffusivity (λ_⊥) were calculated based on whole-brain voxel analysis method. Paired t-test was conducted to evaluate statistical significance between pre-RT and post-RT groups. In the subgroup analysis, all the subjects were divided into 3 groups according to the average dose of temporal lobe, and each group was set with an equal dose interval range. The DTI-related parameters of whole brain pre-RT and post-RT in each group were statistically compared. All the statistical results were corrected by FDR with a threshold of P<0.05 and clusters>100. Results: FA, MD, λ_‖ and λ_⊥in the post-RT group significantly differed compared with those in the pre-RT group (P<0.05). The values of FA, MD, λ_‖ and λ_⊥were 0.455±0.016, (9.893±0.403)×10^-4, (13.441±0.412)×10^-4 and (8.231±0.429)×10^-4, respectively. Subgroup analysis showed that the extent and degree of λ_‖ and λ_⊥ changes were exacerbated with the increase of the average dose of temporal lobe after RT. Particularly in high-dose group, the average dose range was 25-35 Gy and the extent of regions with significant changes was significantly larger than those in the medium-dose (15-25 Gy) and low-dose groups (5-15 Gy)(P<0.05). Conclusions DTI can be utilized to detect" normal" brain tissue microdamage in NPC patients at early stage after RT. The average radiation dose of temporal lobe may be one of the reasons for the severity of cerebral microdamage. In the future, DTI technique may be useful for guiding exposure dose of organs at risk during RT planning and to evaluate the cohort with a high risk of cerebral microdamage at early stage after RT, thereby protecting normal cerebral tissues to the maximum extent.