Antibiotic sensitivity of the bacterial microflora from the sputum of children with acute pneumonia]

Bacteriological analysis of sputum of 598 children with acute pneumonia was performed. Sensivity of 1348 cultures belonging to 8 bacterial species with respect to benzylpenicillin, streptomycin, chloramphenicol, tetracycline, oxytetracycline, chlortetracycline, erythromycin, oleandomycin, neomycin and monomycin was determined. It was shown that the sputum microflora was often resistant to the antibiotics widely used in the medical practice for prolonged periods of time, such as benzylpenicillin, streptomycin, chloramphenicol, tetracyclines. However, it usually remained sunsitive to neomycin, monomycin, erythromycin and oleandomycin. It was found that antibioticogrammes defining the antibiotic choice were of great significance for therapy of acute pneumonia.     

Sputum neutrophils as a biomarker in COPD: findings from the ECLIPSE study

Introduction

The percentage of neutrophils in sputum are increased in COPD patients, and may therefore be a biomarker of airway inflammation. We studied the relationships between sputum neutrophils and FEV₁, health status, exacerbation rates, systemic inflammation and emphysema, and long term variability at 1 year.

Methods

Sputum samples were obtained from 488 COPD patients within the ECLIPSE cohort. 359 samples were obtained at baseline, and 297 after 1 year. 168 subjects provided samples at both visits. Serum interleukin-6 (IL-6), IL-8, surfactant protein D and C-reactive protein levels were measured by immunoassays. Low-dose CT scans evaluated emphysema.

Results

Sputum neutrophil % increased with GOLD stage. There was a weak association between % sputum neutrophils and FEV₁ % predicted (univariate r² = 0.025 and 0.094 at baseline and year 1 respectively, p < 0.05 after multivariate regression). Similar weak but significant associations were observed between neutrophil % and health status measured using the St Georges Respiratory Questionairre. There were no associations between neutrophils and exacerbation rates or emphysema. Associations between sputum neutrophils and systemic biomarkers were non-significant or similarly weak. The mean change over 1 year in neutrophil % was an increase of 3.5%.

Conclusions

Sputum neutrophil measurements in COPD are associated weakly with FEV₁ % predicted and health status. Sputum neutrophil measurements were dissociated from exacerbation rates, emphysema and systemic inflammation.     

冬季肺炎和哮喘急性加重患儿呼吸道微生物多样性

目的 研究冬季肺炎和哮喘患儿呼吸道微生物的多样性。方法 选择2017年11月至2018年1月在我院急诊科治疗的确诊为肺炎和哮喘急性加重的患儿159例,其中肺炎患儿102例,哮喘急性加重患儿57例。选择同时期在本院就诊的无呼吸道疾病患儿88例,设为对照组。检测患儿呼吸道微生物分布情况。结果 肺炎和哮喘患儿呼吸道微生物多样性增加。肺炎患儿菌群丰度前3位的菌属分别是链球菌属、不动杆菌属、克雷伯菌属。哮喘患儿菌群丰度前3位的分别是嗜血杆菌属、莫拉氏菌属、葡萄球菌属。呼吸道病毒检测结果显示,肺炎患儿检出率前3位的病毒分别是肺炎支原体、呼吸道合胞病毒和副流感病毒3型。哮喘患儿病毒检出率前3位的是柯萨奇病毒、呼吸道合胞病毒和肺炎支原体。肺炎患儿肺炎支原体检出率明显高于哮喘患儿,柯萨奇病毒检出率明显低于哮喘患儿。结论 冬季肺炎和哮喘患儿的临床表现和体征较为相似,但是病原微生物检出情况有所不同。病原微生物检出的差异性有助于正确诊断和鉴别儿童肺炎和哮喘。     

Two‐sample nonparametric likelihood inference based on incomplete data with an application to a pneumonia study

The clinical pulmonary infection score (CPIS) and bronchoalveolar lavage (BAL) are important diagnostic variables of pneumonia for forcefully ventilated patients who are susceptible to nosocomial infection. Because of its invasive nature, BAL is performed for patients only if the CPIS is greater than a certain threshold value. Thus, CPIS and BAL are closely related, yet BAL values are substantially missing. In a randomized clinical trial, the control and oral treatment groups were compared based on the outcomes from these procedures. Because of the relevance of both outcomes with respect to evaluating the efficacy of treatments, we propose and examine a nonparametric test based on these outcomes, which employs the empirical likelihood methodology. While efficient parametric methods are available when data are observed incompletely, performing appropriate goodness‐of‐fit tests to justify the parametric assumptions is difficult. Our motivation is to provide an approach based on no particular distributional assumption, which enables us to use all observed bivariate data, whether completed or not in an approximate likelihood manner. A broad Monte Carlo study evaluates the asymptotic properties and efficiency of the proposed method based on various sample sizes and underlying distributions. The proposed technique is applied to a data set from a pneumonia study demonstrating its practical worth.     

Two-sample density-based empirical likelihood tests for incomplete data in application to a pneumonia study

In clinical trials examining the incidence of pneumonia it is a common practice to measure infection via both invasive and non-invasive procedures. In the context of a recently completed randomized trial comparing two treatments the invasive procedure was only utilized in certain scenarios due to the added risk involved, and given that the level of the non-invasive procedure surpassed a given threshold. Hence, what was observed was bivariate data with a pattern of missingness in the invasive variable dependent upon the value of the observed non-invasive observation within a given pair. In order to compare two treatments with bivariate observed data exhibiting this pattern of missingness we developed a semi-parametric methodology utilizing the density-based empirical likelihood approach in order to provide a non-parametric approximation to Neyman-Pearson-type test statistics. This novel empirical likelihood approach has both a parametric and non-parametric components. The non-parametric component utilizes the observations for the non-missing cases, while the parametric component is utilized to tackle the case where observations are missing with respect to the invasive variable. The method is illustrated through its application to the actual data obtained in the pneumonia study and is shown to be an efficient and practical method.     

定量蛋白质组学在急性高原病研究中的应用进展

急性高原病(acute mountain sickness,AMS)是人体急性暴露于高原低压低氧环境后出现多系统生理紊乱的临床综合征。定量蛋白质组学技术可以系统定量并描述机体蛋白质组成和动态变化规律,近年来在多种疾病的预防、诊断、治疗和发生机制等方面研究应用广泛。本文系统综述了定量蛋白质组学技术及其在AMS的预防、诊断、治疗和急进高原习服机制研究中的应用进展,以期为AMS的发病机制、提前干预、临床治疗和AMS的蛋白质组学研究提供参考。     

Selection of control genes for quantitative RT-PCR based on microarray data

Use of internal reference gene(s) is necessary for adequate quantification of target gene expression by RT-PCR. Herein, we elaborated a strategy of control gene selection based on microarray data and illustrated it by analyzing endomyocardial biopsies with acute cardiac rejection and infection. Using order statistics and binomial distribution we evaluated the probability of finding low-varying genes by chance. For analysis, the microarray data were divided into two sample subsets. Among the first 10% of genes with the lowest standard deviations, we found 14 genes common to both subsets. After normalization using two selected genes, high correlation was observed between expression of target genes evaluated by microarray and RT-PCR, and in independent dataset by RT-PCR (r = 0.9, p < 0.001). In conclusion, we showed a simple and reliable strategy of selection and validation of control genes for RT-PCR from microarray data that can be easily applied for different experimental designs and tissues.     

A quantitative study on recovery from acute haemorrhage in adult laboratory rats. I. Blood morphology

We evaluated changes in blood morphology for detecting acute blood loss in laboratory rats. Haematologic indices which are normally used in investigating drug effects on rat blood morphology were examined. Sublethal acute blood loss (25 ml per kg body weight) modified rat blood morphology in a few minutes; the blood picture was normal within two weeks. Blood drawing (usually up to 10 ml per kg b.w.) can modify rat blood morphology within one week. Erythrocyte counts, haemoglobin concentration and haematocrit decreased earliest, reticulocyte counts were changed longest. Comparing our results and literature data the recovery of blood morphology from acute haemorrhage seems to be more rapid in rats than in men.     

Deriving quantitative conclusions from microarray expression data

MOTIVATION: The last few years have seen the development of DNA microarray technology that allows simultaneous measurement of the expression levels of thousands of genes. While many methods have been developed to analyze such data, most have been visualization-based. Methods that yield quantitative conclusions have been diverse and complex. RESULTS: We present two straightforward methods for identifying specific genes whose expression is linked with a phenotype or outcome variable as well as for systematically predicting sample class membership: (1) a conservative, permutation-based approach to identifying differentially expressed genes; (2) an augmentation of K-nearest-neighbor pattern classification. Our analyses replicate the quantitative conclusions of Golub et al. (1999; Science, 286, 531-537) on leukemia data, with better classification results, using far simpler methods. With the breast tumor data of Perou et al. (2000; Nature, 406, 747-752), the methods lend rigorous quantitative support to the conclusions of the original paper. In the case of the lymphoma data in Alizadeh et al. (2000; Nature, 403, 503-511), our analyses only partially support the conclusions of the original authors. AVAILABILITY: The software and supplementary information are available freely to researchers at academic and non-profit institutions at http://cc.ucsf.edu/jain/public     

Characteristic of the etiologic structure of acute enteric infections in adults based on the data from infectious diseases hospital

Study of the etiologic spectrum of sporadic cases of causative agents of acute enteric infections (AEI) in 753 patients aged 15-85 years old using polymerase chain reaction (PCR) was performed in the infectious diseases hospital during 12 months. It was shown that detection of the causative agents of AEI by PCR was 2.2 times more effective than routine microbiologic diagnostics supplemented with test of feces on rotavirus by ELISA method and allowed to detect etiologic agent in 54.3% of the patients. Viral etiology of AEI was determined in 22.6% of the patients. The most significant causative agents of AEI comparable on the rate of detection with salmonella and shigella were genotype 2 noroviruses and group A rotaviruses which were isolated in 10.4 and 8.9% of the patients respectively. Seasonal change of dominating viral pathogens causing diarrheal diseases was noted: predominance of group A rotaviruses during winter-spring period, noroviruses--during spring-summer months, and astroviruses--during fall and in the beginning of winter.     

Prediction of quantitative phenotypes based on genetic networks: a case study in yeast sporulation

Background  

An exciting application of genetic network is to predict phenotypic consequences for environmental cues or genetic perturbations. However, de novo prediction for quantitative phenotypes based on network topology is always a challenging task.     

A score test for the linkage analysis of qualitative and quantitative traits based on identity by descent data from sib-pairs

We propose a general likelihood-based approach to the linkage analysis of qualitative and quantitative traits using identity by descent (IBD) data from sib-pairs. We consider the likelihood of IBD data conditional on phenotypes and test the null hypothesis of no linkage between a marker locus and a gene influencing the trait using a score test in the recombination fraction theta between the two loci. This method unifies the linkage analysis of qualitative and quantitative traits into a single inferential framework, yielding a simple and intuitive test statistic. Conditioning on phenotypes avoids unrealistic random sampling assumptions and allows sib-pairs from differing ascertainment mechanisms to be incorporated into a single likelihood analysis. In particular, it allows the selection of sib-pairs based on their trait values and the analysis of only those pairs having the most informative phenotypes. The score test is based on the full likelihood, i.e. the likelihood based on all phenotype data rather than just differences of sib-pair phenotypes. Considering only phenotype differences, as in Haseman and Elston (1972) and Kruglyak and Lander (1995), may result in important losses in power. The linkage score test is derived under general genetic models for the trait, which may include multiple unlinked genes. Population genetic assumptions, such as random mating or linkage equilibrium at the trait loci, are not required. This score test is thus particularly promising for the analysis of complex human traits. The score statistic readily extends to accommodate incomplete IBD data at the test locus, by using the hidden Markov model implemented in the programs MAPMAKER/SIBS and GENEHUNTER (Kruglyak and Lander, 1995; Kruglyak et al., 1996). Preliminary simulation studies indicate that the linkage score test generally matches or outperforms the Haseman-Elston test, the largest gains in power being for selected samples of sib-pairs with extreme phenotypes.