Objective To investigate the distribution of air microorganisms in soldies′living quarters of one under-ground tunnel during airtight survival training .Methods Anderson sampling was carried out in Area A and Area B ( living quarters) and Area C (a toilet) at designated time and place.After sampling, the culture and identification of microorgan-isms were finished .Results ①In the living quarters of the whole underground tunnel , the total number of bacteria ranged from 125 to 37 800/m3,but it was 2692, 1844 and 2199/m3, respectively in Area A, B and C.The mean number of bac-teria was 2245/m3 .The number of fungi ranged from 0 to 10 017/m3 .The total number of fungi of Area A , B and C was 1064 , 883 and 1011/m3 .The mean number was 986/m3 .②The number of bacteria in the living areas presented three fea-tures:the total bacteria showed overall three peaksin Area A and B, buttwin peaksin Area C.In Area A and B, the number of bacteria exhibited low colony at first but fluctuated heavily later .In Area C, it decreased gradually to the mini-mum,and the fungi showed a wavy and irregular trend .③The air microbial species included cocci ( Micrococcus, Coriolis of Staphylococcus aureus, S.epidermidis and S.equorum) , bacilli ( Acinetobacter baumannii, A.lwoffii and Alcaligenes faeca-lis),and fungi (Mucor and Saccharomyces).Conclusion Although the content of microorganisms was up to the military hygiene standards , it was higher than in the same kind of tunnels .Themulti peakphenomenon of microbial distribution suggests that the change of air microorganisms in tunnels has its own characteristics .Most of the air microorganisms are con-ditioned pathogens that may cause illness if they are not under control .

Objective The in vitro studies of indicators in burn patients with complicated infection have been little studied till now.So this study aims to investigate the change of proliferation of CD64 +neutrophils from the peripheral blood of burn patients in vitro. Methods CD64+neutrophils from peripheral blood of healthy people were isolated and purified, which was followed by stim-ulating its proliferation with inactivated Staphylococcus in vitro.We further analyzed the proliferation index with Modfit 2 analysis soft-ware.86 burn patients were divided into two groups, 44 cases with complicated infection assigned to experimental group, 42 uninfected assigned to controls.We further detect the counts of WBC and the percentage of CD64 +neutrophils, and then analyzed the specificity and sensitivity by using the receiver operating characteristic ( ROC) curves. Results This in vitro study, the average proliferation index of CD64 +cells in experimental wells was significantly higher than controls (6.48 ±0.11 vs 2.63 ±0.02), the difference was statistically significant (P<0.05);the percentage of CD64 +cells in the peripheral blood of patients in experimental group(64.25 ± 13.11%) was significantly higher than patients without infection(16.33 ±2.77%);The sensitivity and specificity of diagnostic meth-od of CD64 +cells for the burn infection were respectively 94.2%and 76.8%, which was superior to the traditional diagnostic meth-od of WBC ( 68.5%, 64.7%) according to ROC curves. Conclusion CD64 + cells in peripheral blood of burn patients complicated by infection increased more significantly and earlier when compared with the traditional diagnostic method, which may be used as a useful diagnostic indicator for burns complicated infection.

A 13-year-old girl presented with multiple recurrent cutaneous plaques for more than six months,which had been aggravated with intermittent fever for five months.No obvious systemic abnormality was found.Dermatological examination revealed multiple,non-ulcerative,painless,infiltrative,indurated,poorly marginated,purple subcutaneous plaques measuring 3-1 1 cm in diameter with slight squamation in bilateral buttocks and lower limbs.Laboratory investigations showed bicytopenia with the white blood cell count being (0.03-3.7) × 109/L and red blood cell count being (2.8-4.4) × 1012/L,a normal platelet count,hypofibrinogenemia (1.79 g/L) and low proportion of natural killer cells (4.6％).Bone marrow smear showed active proliferation of cells,decreased proportion of granulocytes,presence of a few indefinitely classified cells,and phagocytosis.Reticulocytes were easily seen in the bone marrow smear.Pathologically,no obvious abnormality was observed in the epidermis or dermis,while the subcutaneous adipose tissue,especially fat lobules and some interlobular septa,was extensively infiltrated by large-to medium-sized lymphoid cells with pleomorphic and twisted nuclei as well as a small amount of cytoplasm; necrosis and phagocytosis of nuclear debris and lymphocytes were visible.The atypical lymphoid cells stained positive for CD3,T-cell intracellular antigen-1,granzyme B and TCRγδ with partial loss of CD5 and CD7,but negative for CD56,CD4,CD8 and TCRαβ.No Epstein-Barr virus-encoded RNA (EBER) was detected by in situ hybridization.Based on these findings,a diagnosis of primary cutaneous γδ-T cell lymphoma with hemophagocytic syndrome was made.

Objective To assess the integrity and standardization of structured MRI report for rectal cancer of the affiliated hospital of qingdao university,referring to National Comprehensive Cancer Network (NCCN) guidelines for colorectal cancer (Version 2015)and foreign authoritative research results,and put forward some suggestions to improve the quality.Methods A total of 110 structured MRI reports of 107 patients with rectal cancer were included in the study.The inclusion rates of 8 indexes were evaluated,including tumor site,distance from upper to lower border of tumor (DIS),tumor invasive depth (T staging),anal complex staging (A staging),nodal staging (N staging),the circumferential resection margin (CRM),extramural vascular invasion (EMVI) and metastases staging (M staging),which were compared with research results of structured reports in abroad by using Pearson chi-square test.Results There was a significant difference in the description of N staging (x2 =8.424,P＜0.05) between our research and foreign study,in 110 structured MRI reports.There was no significant difference in the description of tumor site (x2 =0.00,P＞0.05),DIS (x2 =0.041,P ＞0.05),T staging (x2 =3.256,P＞0.05) and CRM(x2 =2.957,P＞0.05) between the two groups.A staging,EMVI and M staging were not described.Conclusion Our structured MRI reports for rectal cancer basically meet international research standards.Structured MRI reports have advantages,and deserve to be further studied and promoted.

Objective: To investigate the clinical significance of high definition (HD) MRI rectal lymph node aided diagnostic system based on deep neural network. Methods: The research selected 301 patients with rectal cancer who underwent pelvic HD MRI and reported pelvic lymph node metastasis from July 2016 to December 2017 in Affiliated Hospital of Qingdao University. According to the chronological order, the first 201 cases were used as learning group. The remaining 100 cases were used as verification group. There were 149 males (74.1%) and 52 females in the study group, with an average age of 58.8 years. There were 76 males (76.0%) and 24 females in the validation group, with an average age of 60.2 years. Firstly, Using deep learning technique, researchers trained the 12 060 HD MRI lymph nodes images data of learning group with convolution neural network to simulate the judgment process of radiologists, and established an artificial intelligence automatic recognition system for metastatic lymph nodes of rectal cancer. Then, 6 030 images of the validation group were clinically validated. Artificial intelligence and radiologists simultaneously diagnosed all cases of HD MRI images and made the diagnosis results of metastatic lymph node. Receiver operating characteristic (ROC) curve and area under curve (AUC) were used to compare the diagnostic level of them. Results: After continuous iteration training of the learning group data, the loss function value of artificial intelligence decreased continuously, and the diagnostic error decreased continuously. Among the 6 030 images of verification group, 912 images were considered to exist metastatic lymph nodes in radiologists′ diagnosis and 987 in artificial intelligence diagnosis. There were 772 images having identical diagnostic results of lymph node location and number of metastases with the two methods. Compared with manual diagnosis, the AUC of the intelligent platform was 0.886 2, the diagnostic time of a single case was 10 s, but the average diagnostic time of doctors was 600 s. Conclusion The HD MRI lymph node automatic recognition system based on deep neural network has high accuracy and high efficiency, and has the clinical significance of auxiliary diagnosis.