Objective To investigate the antibiotic resistance of extended-spectrum β-lactamases (ESBLs)-producing bacteria,and the risk factors for patients with hospital-acquired lower respiratory tract infections caused by these bacteria.Methods The clinical data of 80 cases of hospital-acquired lower respiratory tract infections caused by ESBLs + bacteria in the People's Hospital of Qingtian in Zhejiang Province from July 2008 to December 2011 were collected; and 160 cases of nosocomial infection caused by ESBLs- bacteria were randomly selected as controls.Univariate analysis and multivariate logistic regression were used to analyze the risk factors for ESBLs + bacteria infection.The resistance of sixteen antibiotics was detected by K-B method.Results Univariate analysis revealed that the risk factors for nosocomial lower respirator tract infection caused by ESBLs+ bacteria were hospitalization ≥ 10 d,readmission to hospital,oxygen inhalation,invasive operations,using antacid ＞ 7 d,using glucocorticoids ＞ 7 d,using immunosuppressant ＞ 7 d,using third-generation cephalosporins,using fluoroquinolone antibacterials,and the combined use of antibiotics≥3 d.Multivariate logistic regression analysis identified five independent risk faetors:oxygen inhalation (OR =8.613,95％ CI:1.870-39.659),invasive operations (OR =5.900,95％CI:1.885-18.467),using third-generation cephalosporins (OR =7.465,95％ CI:2.364-23.578),using fluoroquinolone antibacterials (OR =4.481,95％ CI:1.197-16.781) and combined use of antibiotics≥3 d (OR =5.346,95％ CI:1.717-16.643).ESBLs + Escherichia coli and Klebsiella pneumoniae strains were sensitive to imipenem,meropenem,cefoperazone /sulbactam and piperacillin/tazobactam (with the resistance rates lower than 30.00％),but were highly resistant to most β-lactam,aminoglycoside,fluoroquinolone and sulfonamide antibacterials.Conclusion ESBLs + isolates were highly resistant to most antibacterials,and hospital-acquired lower respiratory tract infections with ESBLs+ bacteria are mainly related with invasive operations and the use of antibiotics.

Parkinson's disease (PD) is a common neurological disease in elderly people, and its morbidity and mortality are increasing with the advent of global ageing. The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations. To highlight the use of big data for precision PD medicine, we review PD big data and informatics for the translation of basic PD research to clinical applications. We emphasize some key findings in clinically actionable changes, such as susceptibility genetic variations for PD risk population screening, biomarkers for the diagnosis and stratification of PD patients, risk factors for PD, and lifestyles for the prevention of PD. The challenges associated with the collection, storage, and modelling of diverse big data for PD precision medicine and healthcare are also summarized. Future perspectives on systems modelling and intelligent medicine for PD monitoring, diagnosis, treatment, and healthcare are discussed in the end.

Inflammation and lung function decline are the main pathophysiological features of chronic obstructive pulmonary disease (COPD). Acupuncture can improve lung function in patients with COPD, but the underlying mechanisms are not well understood. Orexins (OXs), which are found in peripheral plasma, are neuropeptides that regulate respiration and their levels are related to COPD. Therefore, we hypothesized that acupuncture might alter OXs, reduce lung inflammation and improve lung function in COPD.