Objective To study community morbidity of gastroesophageal reflux cough (GERC),and then establish its procedure of diagnosis. Methods For the patients with chronic cough, on the basis of inquiring medical history and physical examination, chest radiograph, induced sputum, pulmonary ventilation function and airway hyperresponsiveness, blood eosinophilic, IgE,allergens skin test, nose, throat examination,sinus X-ray or pharyngoscope etc was managed. On the basis of the results,patients suspecting GERC was screened out, and then RDQ was performed, extra-esophageal symptoms related performance was inquired and scores were recorded. The patients with scores ≥ 12 were diagnosed as GERC; the patients with scores ＜ 12 were performed diagnosing treatment with proton pump inhibitor (PPI),and patients with positive results were diagnosed as GERC. The materials was analyzed statistically. Results The patients with chronic cough were 430 cases,and the community morbidity of GERC was 22.79%(98/430). RDQ ≥12 scores was 68.37%(67/98),and RDQ ＜ 12 scores was 31.63%(31/98).There was significant difference in extra-esophagus manifestation (P ＜0.01);26 cases with RDQ ＜12 scores were diagnosed as GERC (83.87%),and the rate of GERC in chronic cough was 21.63% (93/430). Conclusions RDQ is a favourable screening test in diagnosing GERC. PPI diagnosing treatment has high sensibility in GERC. It is necessary to establish community diagnosis procedure.

BACKGROUND:Mesenchymal stem cells are found to have the immunoregulatory activities and a potential application prospect in the treatment of autoimmune diseases.
OBJECTIVE:To explore the mechanism of transplanting mesenchymal stems cells on the treatment of multiple sclerosis.
METHODS:The mouse mesenchymal stems cells were prepared, and injected into the al ogenic and syngenic normal mice, to detect the frequency of CD4+CD25+Foxp3+T cells in the spleen, thymus, and lymph nodes by flow cytometry, and to detect the Foxp3, transforming growth factor-β1, and interleukin-10 mRNA in the spleen, thymus, and lymph nodes by reverse transcription-PCR.
RESULTS AND CONCLUSION:Transplantation of mesenchymal stem cells on normal mice led to a significant up-regulation of CD4+CD25+Foxp3+T cells, Foxp3, transforming growth factor-β1, and interleukin-10 mRNA in the spleen, thymus, and lymph nodes both in the al ogenic and syngenic transplant groups. Transplantation of mesenchymal stem cells may be an available method in the treatment of autoimmune diseases, and CD4+CD25+Foxp3+T cell, Foxp3, transforming growth factor-β1, and interleukin-10 may be involved in this process.

OBJECTIVE To investigate the antimicrobial susceptibility of Streptococcus pneumoniae isolated in Yantai and their mechanisms of resistance to macrolides.METHODS Antimicrobial susceptibility of S.pneumoniae was determined by agar dilution method.Phenotypes of macrolide-resistant S.pneumoniae were determined using double disk test with erythromycin and clindamycin disks.ermB And mefE genes were amplified by PCR.RESULTS Among 42 strains of S.pneumoniae,65.0% were intermediate to and no strain was resistant to penicillin.The resistance rates to erythromycin and clindamycin were 93.0%,respectively.Of 41 erythromycin resistantstrains,93.0% were constitutive resistant.ermB Was detected in 40 strains and mefE in 1 strain,both ermB and mefE genes were found in 9 strains.CONCLUSIONS The resistance rate of S.pneumoniae to penicillin is high in Yantai area,the resistance rates to erythromycin and clindamycin are very high.Target modification by ermB methylase is the predominant mechanism in macrolide-resistant S.pneumoniae in Yantai.

Objective To study the feasibility and value of magnetic resonance diffusion tensor imaging (DTI) to monitor non?arteritic anterior ischemic optic neuropathy (NAION). Methods Thirty eight NAION patients (56 eyes) were divided into acute period in 17 eyes, progressive period in 16 eyes and chronic period in 23 eyes at the base of onset time. According to matching principle, 56 eyes in 38 normal controls (NCs) were enrolled. All the patients and NCs underwent MR and DTI scan. The raw data were processed by two experienced radiologists, mean diffusivity (MD), axial diffusivities (λ//), radial diffusivities (λ┴), fractional anisotropy (FA) and Length value were got. The independent sample t test was used for the parameter values between the NAION group and the NCs group. A single factor variance analysis was used to compare the parameters among different stages of NAION group. Results Compared to the NCs group, the values of FA and Length in NAION group were reduced [0.20±0.11 vs 0.31±0.12, (5.85±0.92) vs (65.11± 6.89) mm], and the differences were statistically significant (t=-4.28,-5.25;P<0.05). The values of MD andλ┴were increased [(0.16±0.04)×10-3 vs (0.10±0.04)×10-3 mm2/s, (0.16±0.05)×10-3 vs (0.09±0.03)×10-3 mm2/s] in NAION group and the differences were statistically significant (t=6.83, 7.10;P<0.05). The value of FA and Length in acute period, progressive period and chronic period of the NAION group decreased differently compared to the NCs group. At the same time, the value of MD value and λ┴in the three periods of the NAION group increased compared to the NCs groupand the differences were statistically significant (P<0.05). The value of FA between the acute period, the progressive period, and the chronic period of NAION group were statistically signficant (F=10.88, P<0.05). However, no significant differences were found in the values of MD, λ┴and Length of the NAION group (F=0.23, 0.64, 0.33, 1.38;P=0.79, 0.54, 0.72, 0.27). Conclusion The parameters of DTI can be used to monitor the damage of optic nerve and development in NAION.

Aiming at the problems of individual differences in the asynchrony process of human lower limbs and random changes in stride during walking, this paper proposes a method for gait recognition and prediction using motion posture signals. The research adopts an optimized gated recurrent unit (GRU) network algorithm based on immune particle swarm optimization (IPSO) to establish a network model that takes human body posture change data as the input, and the posture change data and accuracy of the next stage as the output, to realize the prediction of human body posture changes. This paper first clearly outlines the process of IPSO's optimization of the GRU algorithm. It collects human body posture change data of multiple subjects performing flat-land walking, squatting, and sitting leg flexion and extension movements. Then, through comparative analysis of IPSO optimized recurrent neural network (RNN), long short-term memory (LSTM) network, GRU network classification and prediction, the effectiveness of the built model is verified. The test results show that the optimized algorithm can better predict the changes in human posture. Among them, the root mean square error (RMSE) of flat-land walking and squatting can reach the accuracy of 10 ^-3, and the RMSE of sitting leg flexion and extension can reach the accuracy of 10 ^-2. The R ² value of various actions can reach above 0.966. The above research results show that the optimized algorithm can be applied to realize human gait movement evaluation and gait trend prediction in rehabilitation treatment, as well as in the design of artificial limbs and lower limb rehabilitation equipment, which provide a reference for future research to improve patients' limb function, activity level, and life independence ability.
Algorithms ; Gait ; Humans ; Machine Learning ; Neural Networks, Computer ; Walking