Application of holistic liquid chromatography-high resolution mass spectrometry based urinary metabolomics for prostate cancer detection and biomarker discovery

Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS) in combination with orthogonal Hydrophilic Interaction (HILIC) and Reversed Phase (RP) liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition). The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (0.9. In addition, using the receiver operator characteristics (ROC) test, the area under curve (AUC) for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (

Effects of Salinity on Growth and In Vitro Ichthyotoxicity of Three Strains of <i>Karenia mikimotoi</i>

Karenia mikimotoi is one of the most damaging ichthyotoxic dinoflagellate species commonly found in China. However, its growth and ichthyotoxicity responses to salinity changes are still largely unknown. In this study, the growth and ichthyotoxicity of three K. mikimotoi strains, Hong Kong strain KMHK, Japanese strain NIES2411 and New Zealand strain CAWD133, under different salinities (25 to 35 ppt), initial algal densities (5 to 40 thousand cells) and growth phases were investigated. Results indicated that the optimum salinity for all three strains was 30 ppt. The Japanese strain achieved the highest maximum cell densities (cells mL−1) and the New Zealand strain achieved the highest specific growth rate. The Hong Kong and New Zealand strains could not tolerate the low salinity at 25 ppt and the algal cells burst after 3 days of exposure. The average cell widths of all three algal strains in 35 ppt salinity were significantly larger than that in 30 ppt. The acute toxicity test performed on Oncorhynchus mykiss gill cell line RTgill-W1 revealed that the median lethal times for KMHK and NIES2411 were 66.9 and 31.3 min, respectively, and their ichthyotoxicity was significantly affected by algal cell density and growth phase. Nevertheless, CAWD133 did not pose any ichthyotoxicity. The gill cell viability levels at 30 min were reduced from 96 to 61% and 95 to 39% for KMHK and NIES2411, respectively, when the algal cell density increased from 5 × 103 to 4 × 104 algal cells mL−1. Both KMHK and NIES2411 at stationary phase also had higher toxicity than at log phase, with a 27% reduction of gill cell viability, and exerted higher toxicity to the gill cells under extremely low (28 ppt) or high (35 ppt) salinity. These findings demonstrated that the growth–ichthyotoxicity response of Karenia mikimotoi to salinity was not only strain-specific but also depended on its density and growth phase. Study on the effects of salinity on the growth and toxicity of K. mikimotoi is greatly limited. Results from the present study provide valuable insight on the growth and toxicity of different K. mikimotoi strains, which is important in understanding their occurrence of algal bloom and fish-killing action

Effects of Salinity on Growth and In Vitro Ichthyotoxicity of Three Strains of Karenia mikimotoi

Karenia mikimotoi is one of the most damaging ichthyotoxic dinoflagellate species commonly found in China. However, its growth and ichthyotoxicity responses to salinity changes are still largely unknown. In this study, the growth and ichthyotoxicity of three K. mikimotoi strains, Hong Kong strain KMHK, Japanese strain NIES2411 and New Zealand strain CAWD133, under different salinities (25 to 35 ppt), initial algal densities (5 to 40 thousand cells) and growth phases were investigated. Results indicated that the optimum salinity for all three strains was 30 ppt. The Japanese strain achieved the highest maximum cell densities (cells mL&minus;1) and the New Zealand strain achieved the highest specific growth rate. The Hong Kong and New Zealand strains could not tolerate the low salinity at 25 ppt and the algal cells burst after 3 days of exposure. The average cell widths of all three algal strains in 35 ppt salinity were significantly larger than that in 30 ppt. The acute toxicity test performed on Oncorhynchus mykiss gill cell line RTgill-W1 revealed that the median lethal times for KMHK and NIES2411 were 66.9 and 31.3 min, respectively, and their ichthyotoxicity was significantly affected by algal cell density and growth phase. Nevertheless, CAWD133 did not pose any ichthyotoxicity. The gill cell viability levels at 30 min were reduced from 96 to 61% and 95 to 39% for KMHK and NIES2411, respectively, when the algal cell density increased from 5 &times; 103 to 4 &times; 104 algal cells mL&minus;1. Both KMHK and NIES2411 at stationary phase also had higher toxicity than at log phase, with a 27% reduction of gill cell viability, and exerted higher toxicity to the gill cells under extremely low (28 ppt) or high (35 ppt) salinity. These findings demonstrated that the growth&ndash;ichthyotoxicity response of Karenia mikimotoi to salinity was not only strain-specific but also depended on its density and growth phase. Study on the effects of salinity on the growth and toxicity of K. mikimotoi is greatly limited. Results from the present study provide valuable insight on the growth and toxicity of different K. mikimotoi strains, which is important in understanding their occurrence of algal bloom and fish-killing action

Methylation of Protocadherin 10, a Novel Tumor Suppressor, Is Associated With Poor Prognosis in Patients With Gastric Cancer

Background & Aims: By using methylation-sensitive representational difference analysis, we identified protocadherin 10 (PCDH10), a gene that encodes a protocadherin and is silenced in a tumor-specific manner. We analyzed its epigenetic inactivation, biological effects, and prognostic significance in gastric cancer. Methods: Methylation status was evaluated by combined bisulfite restriction analysis and bisulfite sequencing. The effects of PCDH10 re-expression were determined in growth, apoptosis, proliferation, and invasion assays. PCDH10 target genes were identified by complementary DNA microarray analysis. Results: PCDH10 was silenced or down-regulated in 94% (16 of 17) of gastric cancer cell lines; expression levels were restored by exposure to demethylating agents. Re-expression of PCDH10 in MKN45 gastric cancer cells reduced colony formation in vitro and tumor growth in mice; it also inhibited cell proliferation (P < .01), induced cell apoptosis (P < .001), and repressed cell invasion (P < .05), up-regulating the pro-apoptosis genes Fas, Caspase 8, Jun, and CDKN1A; the antiproliferation gene FGFR; and the anti-invasion gene HTATIP2. PCDH10 methylation was detected in 82% (85 of 104) of gastric tumors compared with 37% (38 of 104) of paired nontumor tissues (P < .0001). In the latter, PCDH10 methylation was higher in precancerous lesions (27 of 45; 60%) than in chronic gastritis samples (11 of 59; 19%) (P < .0001). After a median follow-up period of 16.8 months, multivariate analysis revealed that patients with PCDH10 methylation in adjacent nontumor areas had a significant decrease in overall survival. Kaplan-Meier survival curves showed that PCDH10 methylation was associated significantly with shortened survival in stage I-III gastric cancer patients. Conclusions: PCDH10 is a gastric tumor suppressor; its methylation at early stages of gastric carcinogenesis is an independent prognostic factor. © 2009 AGA Institute.link_to_subscribed_fulltex

Additional file 1 of Feasibility and acceptability of electronic EQ-5D-5L for routine measurement of HRQOL in patients with chronic musculoskeletal problems in Hong Kong primary care

Additional file 1: Supplementary Materials on e-EQ-5D-5L platform, study questionnaires, interview guides and qualitative interview subject characteristics

PCA score plots with different normalisation methods.

<p>Cancer subjects are labelled in red, controls in blue and QCs in green. The vector from diamond to 5-point star is labelled in black, to 4-point star in green and to inverted triangle in purple. (A–C) Normalisation to creatinine, MSTUS and osmolality respectively. (D) raw data without normalisation.</p

The statistical results for biomarkers surviving testing against a new cohort of patients.

a<p>: identified by accurate mass and MS² fragmentation.</p>b<p>: only identified by accurate mass in the in-house database.</p>c<p>: only elemental composition predicted formula (<3 ppm).</p

LC-HRMS/MS results of isomers of C₅H₁₀N₂O₃.

<p>Extracted ion chromatograms under 4 different LC-HRMS conditions (A) and the interpretation of their MS² fragmentations (B).</p

Clinicopathological characteristics of the tumor patients.

<p><b>GS = Gleason Score T = T stages N = N stages M = M stages.</b></p

The numbers of remaining features and their percentages after each data filter.

<p>The numbers of remaining features and their percentages after each data filter.</p