Diagnosing lung cancer through metabolic fingerprint based on machine learning / 中华检验医学杂志

Objective:To screen out the differentially regulated metabolites by the analysis of serum metabolic fingerprints, and to provide potential biomarkers for diagnosis of lung cancer.Methods:A total of 228 subjects were enrolled in Changhai Hospital from January 27, 2021 to June 4, 2021, including 97 newly diagnosed lung cancer patients and 131 healthy individuals. Serum samples were collected from the enrolled cohort according to a standard procedure, and the enrolled cohort was divided into a training set and a completely independent validation set by stratified random sampling. The metabolic fingerprints of serum samples were collected by previously developed nano-assisted laser desorption/ionization mass spectrometry (nano-LDI MS). After age and gender matching of the training set, a diagnostic model based on serum metabolic fingerprints was established by machine learning algorithm, and the classification performance of the model was evaluated by receiver operating characteristic (ROC) curve.Results:Serum metabolic fingerprint for each sample was obtained in 1 minute using a novel nano-LDI MS, with consumption of only 1 μl original serum sample. For the training set, the area under ROC curve (AUC) of the constructed classifier for diagnosis of lung cancer was 0.92 (95% CI 0.87-0.97), with a sensitivity of 89% and specificity of 89%. For the independent validation set, the AUC reached 0.96 (95% CI 0.90-1.00) with a sensitivity of 91% and specificity of 94%, which showed no significant decrease compared to training set. We also identified a biomarker panel of 5 metabolites, demonstrating a unique metabolic fingerprint of lung cancer patients. Conclusion:Serum metabolic fingerprints and machine learning were combined to establish a diagnostic model, which can be used to distinguish between lung cancer patients and healthy controls. This work sheds lights on the rapid metabolic analysis for clinical application towards in vitro diagnosis.

Clinical Observation of Posterior Pituitary Injection Combined with Ulinastatin for Injection in the Treat-ment of Severe Lung Contusion / 中国药房

OBJECTIVE:To investigate the therapeutic efficacy and safety of Posterior pituitary injection combined with Ulina-station for injection in the treatment of severe lung contusion. METHODS:In retrospective study,60 patients with severe lung con-tusion in our hospital from Jan. 2015 to May 2016 were divided into control group and observation group according to therapy plan,with 30 cases in each group. Control group was given Ulinastation for injection 100 thousand U+0.9% Sodium chloride injec-tion 100 mL,ivgtt,bid. Observation group was additionally given Posterior pituitary injection 6 U+0.9% Sodium chloride injection 49 mL,intravenous pumping (initial rate was 0.008 U/min,adjusted to ≤0.04 U/min),bid,on the basis of control group. Both groups were treated for 1 week. The respiratory frequency,simple score of pulmonary contusion,chest X-ray score,the levels of arterial blood gas indexes(PaO2,PaCO2,SaO2,PO2/FiO2)and inflammation indexes(IL-2,IL-6,IL-10,hs-CRP,TNF-α)before and after treatment as well as clinical efficacy were observed in 2 groups. The occurrence of ADR was recorded. RESULTS:Before treatment,there was no statistical significance in respiratory frequency,simple score of pulmonary contusion,chest X-ray score, the levels of arterial blood gas index or inflammation indexes between 2 groups(P>0.05). After treatment,respiratory frequency, simple score of pulmonary contusion,chest X-ray score,and the levels of IL-6,hs-CRP,TNF-αin 2 groups were decreased signif-icantly,and the observation group was significantly lower than the control group,with statistical significance(P<0.05). The lev-els of PaO2,PaCO2,SaO2,PO2/FiO2,IL-2 and IL-10 in 2 groups were increased significantly,and the observation group was sig-nificantly higher than the control group,with statistical significance (P<0.05). Total response rate of observation group (100%) was significantly higher than that of control group(86.67%),with statistical significance(P<0.05). The incidence of ADR in con-trol group(13.33%)was significantly higher than observation group(6.67%),with statistical significance(P<0.05). CONCLU-SIONS:Posterior pituitary injection combined with Ulinastatin for injection show good therapeutic efficacy for severe lung contu-sion and effectively inhibit inflammatory reaction with good safety.

Literature Analysis of Moxifloxacin-induced Adverse Drugs Reactions in 3 445 Cases / 中国药房

OBJECTIVE:To investigate the characteristics and regularity of moxifloxacin-induced adverse drug reaction(ADR) and provide reference for the rational clinical use of drugs. METHODS:Retrieved from CNKI (2005-2014) about the moxifloxa-cin-induced ADR,3 445 cases and the related ADR information were statistically analyzed. RESULTS:Moxifloxacin-induced ADR had a certain relationship with gender,and the male had a high incidence,especially the elderly patients. ADR could appear within 10 min;the clinic features were allergic reaction,the nervous system and digestive system at most. CONCLUSIONS:Great impor-tance should be attached to ADR monitoring and rational use of drug to reduce or avoid the occurrences of moxifloxacin-induced ADR.

OsCOI1, a Putative COI1 in Rice, Show MeJA and ABA Dependent Expression / 生物化学与生物物理进展

A novel gene, which was a homologue of Arabidopsis COI1 was isolated from rice (Oryza sativa L.) by RT-PCR and designated as OsCOI1. It encoded a protein of 595 amino acids. The similar F-box motif and 16 leucine-rich repeats were found in the deduced protein OsCOI1. OsCOI1 and COI1 showed high homology (74%) at amino acid level. Semi-quantitative RT-PCR and Northern blot analysis demonstrated that the expression of OsCOI1 in rice varied obviously after treatment with MeJA and ABA but was not affected by SA and ET, suggesting that the specific function of OsCOI1 in JA signal pathway and related ABA pathway.