Epithelial ovarian cancer (EOC) is the most deadly of the gynecological cancers. New approaches and better tools for monitoring treatment efficacy and disease progression of EOC are required. In this study, metabolomics using rapid resolution liquid chromatography mass spectrometry was applied to a systematic investigation of metabolic changes in response to advanced EOC, surgery and recurrence. The results revealed considerable metabolic differences between groups. Moreover, 37, 30, and 26 metabolites were identified as potential biomarkers for primary, surgical and recurrent EOC, respectively. Primary EOC was characterized by abnormal lipid metabolism and energy disorders. Oxidative stress and surgical efficacy were clear in the post-operative EOC patients. Recurrent EOC patients showed increased amino acid and lipid metabolism compared with primary EOC patients. After cytoreductive surgery, eight metabolites (e.g. l-kynurenine, retinol, hydroxyphenyllactic acid, 2-octenoic acid) corrected towards levels of the control group, and four (e.g. hydroxyphenyllactic acid, 2-octenoic acid) went back again to primary EOC levels after disease relapse. In conclusion, this study delineated metabolic changes in response to advanced EOC, surgery and recurrence, and identified biomarkers that could facilitate both understanding and monitoring of EOC development and progression.

Disruption of ionic homeostasis and neuronal hyperexcitability contribute to early brain injury after subarachnoid hemorrhage (SAH).The hyperpolarization-activated/cyclic nucleotide (HCN)-gated channels play critical role in the regulation of neuronal excitability in hippocampus CA1 region and neocortex, in which the abnormal neuronal activities are more readily provoked. This study was to investigate the interactions between HCN channels and hyperneuronal activity after experimental SAH. The present results from wholecell recordings in rat brain slices indicated that (1)

The objective of this study was to evaluate the association betweenthe quantitative assessment of background parenchymal enhancement rate (BPER) and breast cancer. From 14,033 consecutive patients who underwent breast MRI in our center, we randomly selected 101 normal controls. Then, we selected 101 women with benign breast lesions and 101 women with breast cancer who were matched for age and menstruation status. We evaluated BPER at early (2 minutes), medium (4 minutes) and late (6 minutes) enhanced time phases of breast MRI for quantitative assessment. Odds ratios (ORs) for risk of breast cancer were calculated using the receiver operating curve. The BPER increased in a time-dependent manner after enhancement in both premenopausal and postmenopausal women. Premenopausal women had higher BPER than postmenopausal women at early, medium and late enhanced phases. In the normal population, the OR for probability of breast cancer for premenopausal women with high BPER was 4.1 (95% CI: 1.7–9.7) and 4.6 (95% CI: 1.7–12.0) for postmenopausal women. The OR of breast cancer morbidity in premenopausal women with high BPER was 2.6 (95% CI: 1.1–6.4) and 2.8 (95% CI: 1.2–6.1) for postmenopausal women. The BPER was found to be a predictive factor of breast cancer morbidity. Different time phases should be used to assess BPER in premenopausal and postmenopausal women.

IntroductionLung cancer is the most common cancer and the leading cause of cancer death in China, as well as in the world. Late diagnosis is the main obstacle to improving survival. Currently, early detection methods for lung cancer have many limitations, for example, low specificity, risk of radiation exposure and overdiagnosis. Exhaled breath analysis is one of the most promising non-invasive techniques for early detection of lung cancer. The aim of this study is to identify volatile organic compound (VOC) biomarkers in lung cancer and to construct a predictive model for lung cancer based on exhaled breath analysis.Methods and analysisThe study will recruit 389 lung cancer patients in one cancer centre and 389 healthy subjects in two lung cancer screening centres. Bio-VOC breath sampler and Tedlar bag will be used to collect breath samples. Gas chromatography-mass spectrometry coupled with solid phase microextraction technique will be used to analyse VOCs in exhaled breath. VOC biomarkers with statistical significance and showing abilities to discriminate lung cancer patients from healthy subjects will be selected for the construction of predictive model for lung cancer.Ethics and disseminationThe study was approved by the Ethics Committee of Sichuan Cancer Hospital on 6 April 2017 (No. SCCHEC-02-2017-011). The results of this study will be disseminated in presentations at academic conferences, publications in peer-reviewed journals and the news media.Trial registration numberChiCTR-DOD-17011134; Pre-results.